Дисертації з теми "Unmanned Aerial Vehicles Flight Control"
Щоб переглянути інші типи публікацій з цієї теми, перейдіть за посиланням: Unmanned Aerial Vehicles Flight Control.
Оформте джерело за APA, MLA, Chicago, Harvard та іншими стилями
Ознайомтеся з топ-50 дисертацій для дослідження на тему "Unmanned Aerial Vehicles Flight Control".
Біля кожної праці в переліку літератури доступна кнопка «Додати до бібліографії». Скористайтеся нею – і ми автоматично оформимо бібліографічне посилання на обрану працю в потрібному вам стилі цитування: APA, MLA, «Гарвард», «Чикаго», «Ванкувер» тощо.
Також ви можете завантажити повний текст наукової публікації у форматі «.pdf» та прочитати онлайн анотацію до роботи, якщо відповідні параметри наявні в метаданих.
Переглядайте дисертації для різних дисциплін та оформлюйте правильно вашу бібліографію.
1
Peddle, Iain Kenneth. "Acceleration based manoeuvre flight control system for Unmanned Aerial Vehicles /." Link to the online version, 2008. http://hdl.handle.net/10019/1425.
Повний текст джерела
2
Peddle, Iain K. "Acceleration based manoeuvre flight control system for unmanned aerial vehicles." Thesis, Stellenbosch : Stellenbosch University, 2008. http://hdl.handle.net/10019.1/1172.
Повний текст джерелаАнотація:
Thesis (PhD (Electrical and Electronic Engineering))--Stellenbosch University, 2008.A strategy for the design of an effective, practically feasible, robust, computationally efficient autopilot for three dimensional manoeuvre flight control of Unmanned Aerial Vehicles is presented. The core feature of the strategy is the design of attitude independent inner loop acceleration controllers. With these controllers implemented, the aircraft is reduced to a point mass with a steerable acceleration vector when viewed from an outer loop guidance perspective. Trajectory generation is also simplified with reference trajectories only required to be kinematically feasible. Robustness is achieved through uncertainty encapsulation and disturbance rejection at an acceleration level. The detailed design and associated analysis of the inner loop acceleration controllers is carried out for the case where the airflow incidence angles are small. For this case it is shown that under mild practically feasible conditions the inner loop dynamics decouple and become linear, thereby allowing the derivation of closed form pole placement solutions. Dimensional and normalised non-dimensional time variants of the inner loop controllers are designed and their respective advantages highlighted. Pole placement constraints that arise due to the typically weak non-minimum phase nature of aircraft dynamics are developed. A generic, aircraft independent guidance control algorithm, well suited for use with the inner loop acceleration controllers, is also presented. The guidance algorithm regulates the aircraft about a kinematically feasible reference trajectory. A number of fundamental basis trajectories are presented which are easily linkable to form complex three dimensional manoeuvres. Results from simulations with a number of different aircraft and reference trajectories illustrate the versatility and functionality of the autopilot. Key words: Aircraft control, Autonomous vehicles, UAV flight control, Acceleration control, Aircraft guidance, Trajectory tracking, Manoeuvre flight control.
3
Drozeski, Graham R. "A Fault-Tolerant Control Architecture for Unmanned Aerial Vehicles." Diss., Georgia Institute of Technology, 2005. http://hdl.handle.net/1853/7523.
Повний текст джерелаАнотація:
Research has presented several approaches to achieve varying degrees of fault-tolerance in unmanned aircraft. Approaches in reconfigurable flight control are generally divided into two categories: those which incorporate multiple non-adaptive controllers and switch between them based on the output of a fault detection and identification element and those that employ a single adaptive controller capable of compensating for a variety of fault modes. Regardless of the approach for reconfigurable flight control, certain fault modes dictate system restructuring in order to prevent a catastrophic failure. System restructuring enables active control of actuation not employed by the nominal system to recover controllability of the aircraft. After system restructuring, continued operation requires the generation of flight paths that adhere to an altered flight envelope. The control architecture developed in this research employs a multi-tiered hierarchy to allow unmanned aircraft to generate and track safe flight paths despite the occurrence of potentially catastrophic faults. The hierarchical architecture increases the level of autonomy of the system by integrating five functionalities with the baseline system: fault detection and identification, active system restructuring, reconfigurable flight control, reconfigurable path planning, and mission adaptation. Fault detection and identification algorithms continually monitor aircraft performance and issue fault declarations. When the severity of a fault exceeds the capability of the baseline flight controller, active system restructuring expands the controllability of the aircraft using unconventional control strategies not exploited by the baseline controller. Each of the reconfigurable flight controllers and the baseline controller employ a proven adaptive neural network control strategy. A reconfigurable path planner employs an adaptive model of the vehicle to re-shape the desired flight path. Generation of the revised flight path is posed as a linear program constrained by the response of the degraded system. Finally, a mission adaptation component estimates limitations on the closed-loop performance of the aircraft and adjusts the aircraft mission accordingly. A combination of simulation and flight test results using two unmanned helicopters validates the utility of the hierarchical architecture.
4
Pietersen, Willem Hermanus. "System identification for fault tolerant control of unmanned aerial vehicles." Thesis, Stellenbosch : University of Stellenbosch, 2010. http://hdl.handle.net/10019.1/4164.
Повний текст джерелаАнотація:
Thesis (MScEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2010.ENGLISH ABSTRACT: In this project, system identification is done on the Modular Unmanned Aerial Vehicle (UAV). This is necessary to perform fault detection and isolation, which is part of the Fault Tolerant Control research project at Stellenbosch University. The equations necessary to do system identification are developed. Various methods for system identification is discussed and the regression methods are implemented. It is shown how to accommodate a sudden change in aircraft parameters due to a fault. Smoothed numerical differentiation is performed in order to acquire data necessary to implement the regression methods. Practical issues regarding system identification are discussed and methods for addressing these issues are introduced. These issues include data collinearity and identification in a closed loop. The regression methods are implemented on a simple roll model of the Modular UAV in order to highlight the various difficulties with system identification. Different methods for accommodating a fault are illustrated. System identification is also done on a full nonlinear model of the Modular UAV. All the parameters converges quickly to accurate values, with the exception of Cl R , CnP and Cn A . The reason for this is discussed. The importance of these parameters in order to do Fault Tolerant Control is also discussed. An S-function that implements the recursive least squares algorithm for parameter estimation is developed. This block accommodates for the methods of applying the forgetting factor and covariance resetting. This block can be used as a stepping stone for future work in system identification and fault detection and isolation.
AFRIKAANSE OPSOMMING: In hierdie projek word stelsel identifikasie gedoen op die Modulêre Onbemande Vliegtuig. Dit is nodig om foutopsporing en isolasie te doen wat ’n deel uitmaak van fout verdraagsame beheer. Die vergelykings wat nodig is om stelsel identifikasie te doen is ontwikkel. Verskeie metodes om stelsel identifikasie te doen word bespreek en die regressie metodes is uitgevoer. Daar word gewys hoe om voorsiening te maak vir ’n skielike verandering in die vliegtuig parameters as gevolg van ’n fout. Reëlmatige numeriese differensiasie is gedoen om data te verkry wat nodig is vir die uitvoering van die regressie metodes. Praktiese kwessies aangaande stelsel identifikasie word bespreek en metodes om hierdie kwessies aan te spreek word gegee. Hierdie kwessies sluit interafhanklikheid van data en identifikasie in ’n geslote lus in. Die regressie metodes word toegepas op ’n eenvoudige rol model van die Modulêre Onbemande Vliegtuig om die verskeie kwessies aangaande stelsel identifikasie uit te wys. Verskeie metodes vir die hantering vir ’n fout word ook illustreer. Stelsel identifikasie word ook op die volle nie-lineêre model van die Modulêre Onbemande Vliegtuig gedoen. Al die parameters konvergeer vinnig na akkurate waardes, met die uitsondering van Cl R , CnP and Cn A . Die belangrikheid van hierdie parameters vir fout verdraagsame beheer word ook bespreek. ’n S-funksie blok vir die rekursiewe kleinste-kwadraat algoritme is ontwikkel. Hierdie blok voorsien vir die metodes om die vergeetfaktor en kovariansie herstelling te implementeer. Hierdie blok kan gebruik word vir toekomstige werk in stelsel identifikasie en foutopsporing en isolasie.
5
Karlsson, Mia. "Control of Unmanned Aerial Vehicles using Non-linear Dynamic Inversion." Thesis, Linköping University, Department of Electrical Engineering, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-1519.
Повний текст джерелаАнотація:
This master's thesis deals with the control design method called Non-linear Dynamic Inversion (NDI) and how it can be applied to Unmanned Aerial Vehicles (UAVs). In this thesis, simulations are conducted using a model for the unmanned aerial vehicle SHARC (Swedish Highly Advanced Research Configuration), which Saab AB is developing.
The idea with NDI is to cancel the non-linear dynamics and then the system can be controlled as a linear system. This design method needs much information about the system, or the output will not be as desired. Since it is impossible to know the exact mathematical model of a system, some kind of robust control theory is needed. In this thesis integral action is used.
A problem with NDI is that the mathematical model of a system is often very complex, which means that the controller also will be complex. Therefore, a controller that uses pure NDI is only discussed, and the simulations are instead based on approximations that use a cascaded NDI. Two such methods are investigated. One that uses much information from aerodata tables, and one that uses the derivatives of some measured outputs. Both methods generate satisfying results. The outputs from the second method are more oscillatory but the method is found to be more robust. If the signals are noisy, indications are that method one will be better.
6
De, Hart Ruan Dirk. "Advanced take-off and flight control algorithms for fixed wing unmanned aerial vehicles." Thesis, Stellenbosch : University of Stellenbosch, 2010. http://hdl.handle.net/10019.1/4179.
Повний текст джерелаАнотація:
Thesis (MScEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2010.ENGLISH ABSTRACT: This thesis presents the development and implementation of a position based kinematic guidance system, the derivation and testing of a Dynamic Pursuit Navigation algorithm and a thorough analysis of an aircraft’s runway interactions, which is used to implement automated take-off of a fixed wing UAV. The analysis of the runway is focussed on the aircraft’s lateral modes. Undercarriage and aerodynamic effects are first analysed individually, after which the combined system is analysed. The various types of feedback control are investigated and the best solution suggested. Supporting controllers are designed and combined to successfully implement autonomous take-off, with acceleration based guidance. A computationally efficient position based kinematic guidance architecture is designed and implemented that allows a large percentage of the flight envelope to be utilised. An airspeed controller that allows for aggressive flight is designed and implemented by applying Feedback Linearisation techniques. A Dynamic Pursuit Navigation algorithm is derived that allows following of a moving ground based object at a constant distance (radius). This algorithm is implemented and verified through non-linear simulation.
AFRIKAANSE OPSOMMING: Hierdie tesis handel oor die ontwikkeling en toepassing van posisie-afhanklike, kinematiese leidings-algoritmes, die ontwikkeling van ’n Dinamiese Volgings-navigasie-algoritme en ’n deeglike analise van die interaksie van ’n lugraam met ’n aanloopbaan sodat outonome opstygprosedure van ’n vastevlerk vliegtuig bewerkstellig kan word. Die bogenoemde analise het gefokus op die laterale modus van ’n vastevlerk vliegtuig en is tweeledig behartig. Die eerste gedeelte het gefokus op die analise van die onderstel, terwyl die lugraam en die aerodinamiese effekte in die tweede gedeelte ondersoek is. Verskillende tipes terugvoerbeheer vir die outonome opstygprosedure is ondersoek om die mees geskikte tegniek te bepaal. Addisionele beheerders, wat deur die versnellingsbeheer gebaseerde opstygprosedure benodig word, is ontwerp. ’n Posisie gebaseerde kinematiese leidingsbeheerstruktuur om ’n groot persentasie van die vlugvermoë te benut, is ontwikkel. Terugvoer linearisering is toegepas om ’n lugspoedbeheerder , wat in staat is tot aggressiewe vlug, te ontwerp. ’n Dinamiese Volgingsnavigasie-algoritme wat in staat is om ’n bewegende grondvoorwerp te volg, is ontwikkel. Hierdie algoritme is geïmplementeer en bevestig deur nie-lineêre simulasie.
7
Kang, Keeryun. "Online optimal obstacle avoidance for rotary-wing autonomous unmanned aerial vehicles." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/44820.
Повний текст джерелаАнотація:
This thesis presents an integrated framework for online obstacle avoidance of rotary-wing unmanned aerial vehicles (UAVs), which can provide UAVs an obstacle field navigation capability in a partially or completely unknown obstacle-rich environment. The framework is composed of a LIDAR interface, a local obstacle grid generation, a receding horizon (RH) trajectory optimizer, a global shortest path search algorithm, and a climb rate limit detection logic.
The key feature of the framework is the use of an optimization-based trajectory generation in which the obstacle avoidance problem is formulated as a nonlinear trajectory optimization problem with state and input constraints over the finite range of the sensor. This local trajectory optimization is combined with a global path search algorithm which provides a useful initial guess to the nonlinear optimization solver. Optimization is the natural process of finding the best trajectory that is dynamically feasible, safe within the vehicle's flight envelope, and collision-free at the same time. The optimal trajectory is continuously updated in real time by the numerical optimization solver, Nonlinear Trajectory Generation (NTG), which is a direct solver based on the spline approximation of trajectory for dynamically flat systems. In fact, the overall approach of this thesis to finding the optimal trajectory is similar to the model predictive control (MPC) or the receding horizon control (RHC), except that this thesis followed a two-layer design; thus, the optimal solution works as a guidance command to be followed by the controller of the vehicle.
The framework is implemented in a real-time simulation environment, the Georgia Tech UAV Simulation Tool (GUST), and integrated in the onboard software of the rotary-wing UAV test-bed at Georgia Tech. Initially, the 2D vertical avoidance capability of real obstacles was tested in flight. Then the flight test evaluations were extended to the benchmark tests for 3D avoidance capability over the virtual obstacles, and finally it was demonstrated on real obstacles located at the McKenna MOUT site in Fort Benning, Georgia. Simulations and flight test evaluations demonstrate the feasibility of the developed framework for UAV applications involving low-altitude flight in an urban area.
8
Grymin, David J. "Development of a novel method for autonomous navigation and landing of unmanned aerial vehicles /." Online version of thesis, 2009. http://hdl.handle.net/1850/10615.
Повний текст джерела
9
Kriel, Steven Cornelius. "A comparison of control systems for the flight transition of VTOL unmanned aerial vehicles." Thesis, Link to the online version, 2008. http://hdl.handle.net/10019/1334.
Повний текст джерела
10
Ward, Garrett. "Design of a Small Form-Factor Flight Control System." VCU Scholars Compass, 2014. http://scholarscompass.vcu.edu/etd/3448.
Повний текст джерелаАнотація:
This work outlines a design for a small form-factor flight control system designed to fly in a wide variety of airframes. The system was designed with future expansion in mind while providing a complete, all-in-one solution to meet present needs. This system as presented meets most needs while remaining relatively low cost. It has a completely integrated IMU solution as well as on- board GPS. It is capable of basic waypoint navigation. This solution was testing using software and hardware-in-the-loop simulation which proved its functionality.
11
Casey, Julian L. "Analytical approach to multi-objective joint inference control for fixed wing unmanned aerial vehicles." Wright State University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright160431245463856.
Повний текст джерела
12
Puttige, Vishwas Ramadas Engineering & Information Technology Australian Defence Force Academy UNSW. "Neural network based adaptive control for autonomous flight of fixed wing unmanned aerial vehicles." Awarded by:University of New South Wales - Australian Defence Force Academy. Engineering & Information Technology, 2009. http://handle.unsw.edu.au/1959.4/43736.
Повний текст джерелаАнотація:
This thesis presents the development of small, inexpensive unmanned aerial vehicles (UAVs) to achieve autonomous fight. Fixed wing hobby model planes are modified and instrumented to form experimental platforms. Different sensors employed to collect the flight data are discussed along with their calibrations. The time constant and delay for the servo-actuators for the platform are estimated. Two different data collection and processing units based on micro-controller and PC104 architectures are developed and discussed. These units are also used to program the identification and control algorithms. Flight control of fixed wing UAVs is a challenging task due to the coupled, time-varying, nonlinear dynamic behaviour. One of the possible alternatives for the flight control system is to use the intelligent adaptive control techniques that provide online learning capability to cope with varying dynamics and disturbances. Neural network based indirect adaptive control strategy is applied for the current work. The two main components of the adaptive control technique are the identification block and the control block. Identification provides a mathematical model for the controller to adapt to varying dynamics. Neural network based identification provides a black-box identification technique wherein a suitable network provides prediction capability based upon the past inputs and outputs. Auto-regressive neural networks are employed for this to ensure good retention capabilities for the model that uses the past outputs and inputs along with the present inputs. Online and offline identification of UAV platforms are discussed based upon the flight data. Suitable modifications to the Levenberg-Marquardt training algorithm for online training are proposed. The effect of varying the different network parameters on the performance of the network are numerically tested out. A new performance index is proposed that is shown to improve the accuracy of prediction and also reduces the training time for these networks. The identification algorithms are validated both numerically and flight tested. A hardware-in-loop simulation system has been developed to test the identification and control algorithms before flight testing to identify the problems in real time implementation on the UAVs. This is developed to keep the validation process simple and a graphical user interface is provided to visualise the UAV flight during simulations. A dual neural network controller is proposed as the adaptive controller based upon the identification models. This has two neural networks collated together. One of the neural networks is trained online to adapt to changes in the dynamics. Two feedback loops are provided as part of the overall structure that is seen to improve the accuracy. Proofs for stability analysis in the form of convergence of the identifier and controller networks based on Lyapunov's technique are presented. In this analysis suitable bounds on the rate of learning for the networks are imposed. Numerical results are presented to validate the adaptive controller for single-input single-output as well as multi-input multi-output subsystems of the UAV. Real time validation results and various flight test results confirm the feasibility of the proposed adaptive technique as a reliable tool to achieve autonomous flight. The comparison of the proposed technique with a baseline gain scheduled controller both in numerical simulations as well as test flights bring out the salient adaptive feature of the proposed technique to the time-varying, nonlinear dynamics of the UAV platforms under different flying conditions.
13
Acuna, Virgilio. "Using Unmanned Aerial Vehicles for Wireless Localization in Search and Rescue." FIU Digital Commons, 2017. https://digitalcommons.fiu.edu/etd/3646.
Повний текст джерелаАнотація:
This thesis presents how unmanned aerial vehicles (UAVs) can successfully assist in search and rescue (SAR) operations using wireless localization. The zone-grid to partition to capture/detect WiFi probe requests follows the concepts found in Search Theory Method. The UAV has attached a sensor, e.g., WiFi sniffer, to capture/detect the WiFi probes from victims or lost people’s smartphones. Applying the Random-Forest based machine learning algorithm, an estimation of the user's location is determined with a 81.8% accuracy.
UAV technology has shown limitations in the navigational performance and limited flight time. Procedures to optimize these limitations are presented. Additionally, how the UAV is maneuvered during flight is analyzed, considering different SAR flight patterns and Li-Po battery consumption rates of the UAV. Results show that controlling the UAV by remote-controll detected the most probes, but it is less power efficient compared to control it autonomously.
14
Hough, Willem J. "Autonomous aerobatic flight of a fixed wing unmanned aerial vehicle." Thesis, Link to online version, 2007. http://hdl.handle.net/10019/428.
Повний текст джерела
15
Zhou, Yan. "Development of a data collection system for small Unmanned Aerial Vehicles (UAVs)." Thesis, Cape Peninsula University of Technology, 2011. http://hdl.handle.net/20.500.11838/1299.
Повний текст джерелаАнотація:
Dissertation (MTech (Mechanical Engineering))--Cape Peninsula University of Technology, 2011This paper presents the development of a data collection system for a small unmanned Aerial Vehicle (UAV) flight. The following three facets comprise of a UAV system: (1) a UAV aircraft; (2) onboard avionics; and (3) a ground control station subsystem (Taha et al., 2010:1). In this project, the UAV aircraft is based on the low-cost autonomous quad-rotator system named “Arducopter Quad”, where the onboard avionic system utilizes both an ArduPilot Mega (APM) on-board controller and IMU sensor shield, while the “Mission Planner” software operates as GCS software to gather essential flight data (Xiang & Tian, 2011:176). The approach provides the UAV system structure and both hardware and software with a small UAV data collection system, which is examined throughout the study. And introduce the concept of Arducopter dynamics for better understanding with its flight control. The study also considers the communication process between the UAV and the ground control station. The radio wave is an important aspect in the UAV data collection system (Austin, 2010:143). The literature review introduced the basis of the radio wave in respect of its travelling speed, and its characteristics of propagation, including how different frequencies will affect radio wave propagation. The aim of this project was to develop a platform for a small UAV real-time data collection system. The pendulum system was involved to simulate the “Roll” movement of the small UAV, while real-time IMU sensor data was successfully collected at ground control station (GCS), both serial communication and wireless communication, which was applied in the data collection process. The microwave generator interference test proves that the 2.4 GHz XBee module is capable of establishing reliable indoor communication between the APM controller and the GCS. The work of this project is towards development of additional health monitoring technology to prevent the safety issue of the small UAV. The data collection system can be used as basis for the future research of real-time health monitoring for various small UAVs.
16
Gaum, Dunross Rudi. "Agressive flight control techniques for a fixed wing unmanned aerial vehicle." Stellenbosch : University of Stellenbosch, 2009. http://hdl.handle.net/10019.1/3112.
Повний текст джерелаАнотація:
Thesis (MScEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2009.This thesis investigates aggressive all-attitude flight control systems. These are flight controllers capable of controlling an aircraft at any attitude and will enable the autonomous execution of manoeuvres such as high bank angle turns, steep climbs and aerobatic flight manoeuvres. This class of autopilot could be applied to carry out evasive combat manoeuvres or to create more efficient and realistic target drones. A model for the aircraft’s dynamics is developed in such a way that its high bandwidth specific force and moment model is split from its lower bandwidth kinematic model. This split is done at the aircraft’s specific acceleration and roll rate, which enables the design of simple, decoupled, linear attitude independent inner loop controllers to regulate these states. Two outer loop kinematic controllers are then designed to interface with these inner loop controllers to guide the aircraft through predefined reference trajectories. The first method involves the design of a linear quadratic regulator (LQR) based on the successively linearised kinematics, to optimally control the system. The second method involves specific acceleration matching (SAM) and results in a linear guidance controller that makes use of position based trajectories. These position based trajectories allow the aircraft’s velocity magnitude to be regulated independently of the trajectory tracking. To this end, two velocity regulation algorithms were developed. These involved methods of optimal control, implemented using dynamic programming, and energy analysis to regulate the aircraft’s velocity in a predictive manner and thereby providing significantly improved velocity regulation during aggressive aerobatic type manoeuvres. Hardware in the loop simulations and practical flight test data verify the theoretical results of all controllers presented
17
Doepke, Edward Brady. "DESIGN AND FLIGHT TESTING OF A WARPING WING FOR AUTONOMOUS FLIGHT CONTROL." UKnowledge, 2012. http://uknowledge.uky.edu/me_etds/20.
Повний текст джерелаАнотація:
Inflatable-wing Unmanned Aerial Vehicles (UAVs) have the ability to be packed in a fraction of their deployed volume. This makes them ideal for many deployable UAV designs, but inflatable wings can be flexible and don’t have conventional control surfaces. This thesis will investigate the use of wing warping as a means of autonomous control for inflatable wings. Due to complexities associated with manufacturing inflatable structures a new method of rapid prototyping deformable wings is used in place of inflatables to decrease cost and design-cycle time. A UAV testbed was developed and integrated with the warping wings and flown in a series of flight tests. The warping wing flew both under manual control and autopilot stabilization.
18
Sleeman, William Clifford IV. "The Development of a Linux and FPGA Based Autopilot System for Unmanned Aerial Vehicles." VCU Scholars Compass, 2007. http://scholarscompass.vcu.edu/etd_retro/129.
Повний текст джерелаАнотація:
This project is part of research funded by NASA Langley in field of Unmanned Aerial Vehicles (UAVs) and is based on past work conducted at Virginia Commonwealth University. Dr. Mark A. Motter of NASA Langley intends to use the new autopilot system to test aircraft with many control surfaces. The goal of this project is to port an existing UAV autopilot system that has more computing power than the previous generation system to allow for more advanced flight control algorithms.The steps taken to complete this project include choosing a new hardware platform, porting C flight control software from a MicroBlaze platform to a PowerPC platform, and developing FPGA based hardware to interface with external sensors. The Suzaku-V based system was shown to have much better computing performance than the previous system, and several successful test flights have proved the viability of the new autopilot system.
19
Karakas, Deniz. "Nonlinear Modeling And Flight Control System Design Of An Unmanned Aerial Vehicle." Master's thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/3/12608926/index.pdf.
Повний текст джерелаАнотація:
The nonlinear simulation model of an unmanned aerial vehicle (UAV) in MATLAB®/Simulink®
environment is developed by taking into consideration all the possible major system components such as actuators, gravity, engine, atmosphere, wind-turbulence models, as well as the aerodynamics components in the 6 DOF equations of motion. Trim and linearization of the developed nonlinear model are accomplished and various related analyses are carried out. The model is validated by comparing with a similar UAV data in terms of open loop dynamic stability characteristics. Using two main approaches
namely, classical and optimal, linear controllers are designed. For the classical approach, Simulink Response Optimization (SRO) tool of MATLAB®
/Simulink®
is utilized, whereas for the optimal controller approach, linear quadratic (LQ) controller design method is implemented, again by the help of the tools put forth by MATLAB®
. The controllers are designed for control of roll, heading, coordinated turn, flight path, pitch, altitude, and airspeed, i.e., for the achievement of all low-level control functions. These linear controllers are integrated into the nonlinear model, by carrying out gain scheduling with respect to airspeed and altitude, controller input linearization regarding the perturbed states and control inputs, and anti integral wind-up scheme regarding the possible wind-up of the integrators in the controller structures. The responses of the nonlinear model controlled with the two controllers are compared based on the military flight control requirements. The advantages and disadvantages of these two frequently used controllers in industry are investigated and discussed. These results are to be evaluated by the designers themselves based on the design criteria of a project that is worked on.
20
Techy, Laszlo. "Flight Vehicle Control and Aerobiological Sampling Applications." Diss., Virginia Tech, 2009. http://hdl.handle.net/10919/29680.
Повний текст джерелаАнотація:
Aerobiological sampling using unmanned aerial vehicles (UAVs) is an exciting research field blending various scientific and engineering disciplines. The biological data collected using UAVs helps to better understand the atmospheric transport of microorganisms. Autopilot-equipped UAVs can accurately sample along pre-defined flight plans and precisely regulated altitudes. They can provide even greater utility when they are networked together in coordinated sampling missions: such measurements can yield further information about the aerial transport process.
In this work flight vehicle path planning, control and coordination strategies are considered for unmanned autonomous aerial vehicles. A time-optimal path planning algorithm, that is simple enough to be solved in real time, is derived based on geometric concepts. The method yields closed-form solution for an important subset of candidate extremal paths; the rest of the paths are found using a simple numerical root-finding algorithm. A multi-UAV coordination framework is applied to a specific control-volume sampling problem that supports aerobiological data-collection efforts conducted in the lower atmosphere.
The work is part of a larger effort that focuses on the validation of atmospheric dispersion models developed to predict the spread of plant diseases in the lower atmosphere. The developed concepts and methods are demonstrated by field experiments focusing on the spread of the plant pathogen Phytophthora infestans.Ph. D.
21
Ducard, Guillaume Jacques Joseph. "Fault-tolerant flight control and guidance systems for a small unmanned aerial vehicle /." Zürich : ETH, 2007. http://e-collection.ethbib.ethz.ch/show?type=diss&nr=17505.
Повний текст джерела
22
Blaauw, Deon. "Flight control system for a variable stability blended-wing-body unmanned aerial vehicle." Thesis, Stellenbosch : University of Stellenbosch, 2009. http://hdl.handle.net/10019.1/2297.
Повний текст джерелаАнотація:
Thesis (MScEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2009.This thesis presents the analysis, design, simulation and practical implementation of a novel control system for a variable stability blended-wing-body unmanned aerial vehicle. The aircraft has a moveable centre of mass that allows it to operate in an aerodynamically optimised minimum drag configuration during cruise flight. The primary purpose of the control system is thus to regain nominal static stability for all centre of mass positions, and then to further regulate motion variables for autonomous way point navigation. A thorough analysis of the parameters affected by the varying centre of mass position leads to the identification of the main control problem. It is shown that a recently published acceleration based control methodology can be used with minor modification to elegantly solve the variable stability control problem. After providing the details of the control system design, the customised avionics used for their practical implementation are presented. The results of extensive hardware in the loop simulations verify the functionality of the controllers. Finally, flight test results illustrate the practical success of the autopilot and clearly show how the control system is capable of controlling the variable stability aircraft at centre of mass locations where a human pilot could not.
23
Hayes, Edwin Laurie. "Machine Learning for Intelligent Control: Application of Reinforcement Learning Techniques to the Development of Flight Control Systems for Miniature UAV Rotorcraft." Thesis, University of Canterbury. Department of Mechanical Engineering, 2013. http://hdl.handle.net/10092/7810.
Повний текст джерелаАнотація:
This thesis investigates the possibility of using reinforcement learning (RL) techniques to create a flight controller for a quadrotor Micro Aerial Vehicle (MAV).
A capable flight control system is a core requirement of any unmanned aerial vehicle. The challenging and diverse applications in which MAVs are destined to be used, mean that considerable time and effort need to be put into designing and commissioning suitable flight controllers. It is proposed that reinforcement learning, a subset of machine learning, could be used to address some of the practical difficulties.
While much research has delved into RL in unmanned aerial vehicle applications, this work has tended to ignore low level motion control, or been concerned only in off-line learning regimes. This thesis addresses an area in which accessible information is scarce: the performance of RL
when used for on-policy motion control.
Trying out a candidate algorithm on a real MAV is a simple but expensive proposition. In place of such an approach, this research details the development of a suitable simulator environment, in which a prototype controller might be evaluated. Then inquiry then proposes a possible RL-based control system, utilising the Q-learning algorithm, with an adaptive RBF-network providing function approximation.
The operation of this prototypical control system is then tested in detail, to determine both the absolute level of performance which can be expected, and the effect which tuning critical parameters of the algorithm has on the functioning of the controller. Performance is compared against a conventional PID controller to maximise the usability of the results by a wide audience. Testing considers behaviour in the presence of disturbances, and run-time changes in plant dynamics.
Results show that given sufficient learning opportunity, a RL-based control system performs as well as a simple PID controller. However, unstable behaviour during learning is an issue for future analysis.
Additionally, preliminary testing is performed to evaluate the feasibility of implementing RL algorithms in an embedded computing environment, as a general requirement for a MAV flight controller. Whilst the algorithm runs successfully in an embedded context, observation reveals
further development would be necessary to reduce computation time to a level where a controller was able to update sufficiently quickly for a real-time motion control application.
In summary, the study provides a critical assessment of the feasibility of using RL algorithms for motion control tasks, such as MAV flight control. Advantages which merit interest are exposed, though practical considerations suggest at this stage, that such a control system is not a realistic proposition. There is a discussion of avenues which may uncover possibilities to surmount these challenges. This investigation will prove useful for engineers interested in the opportunities which reinforcement learning techniques represent.
24
Mercado-Ravell, Diego Alberto. "Autonomous navigation and teleoperation of unmanned aerial vehicles using monocular vision." Thesis, Compiègne, 2015. http://www.theses.fr/2015COMP2239/document.
Повний текст джерелаАнотація:
Ce travail porte, de façon théorétique et pratique, sur les sujets plus pertinents autour des drones en navigation autonome et semi-autonome. Conformément à la nature multidisciplinaire des problèmes étudies, une grande diversité des techniques et théories ont été couverts dans les domaines de la robotique, l’automatique, l’informatique, la vision par ordinateur et les systèmes embarques, parmi outres.Dans le cadre de cette thèse, deux plates-formes expérimentales ont été développées afin de valider la théorie proposée pour la navigation autonome d’un drone. Le premier prototype, développé au laboratoire, est un quadrirotor spécialement conçu pour les applications extérieures. La deuxième plate-forme est composée d’un quadrirotor à bas coût du type AR.Drone fabrique par Parrot. Le véhicule est connecté sans fil à une station au sol équipé d’un système d’exploitation pour robots (ROS) et dédié à tester, d’une façon facile, rapide et sécurisé, les algorithmes de vision et les stratégies de commande proposés. Les premiers travaux développés ont été basés sur la fusion de donnés pour estimer la position du drone en utilisant des capteurs inertiels et le GPS. Deux stratégies ont été étudiées et appliquées, le Filtre de Kalman Etendu (EKF) et le filtre à Particules (PF). Les deux approches prennent en compte les mesures bruitées de la position de l’UAV, de sa vitesse et de son orientation. On a réalisé une validation numérique pour tester la performance des algorithmes. Une tâche dans le cahier de cette thèse a été de concevoir d’algorithmes de commande pour le suivi de trajectoires ou bien pour la télé-opération. Pour ce faire, on a proposé une loi de commande basée sur l’approche de Mode Glissants à deuxième ordre. Cette technique de commande permet de suivre au quadrirotor de trajectoires désirées et de réaliser l’évitement des collisions frontales si nécessaire. Etant donné que la plate-forme A.R.Drone est équipée d’un auto-pilote d’attitude, nous avons utilisé les angles désirés de roulis et de tangage comme entrées de commande. L’algorithme de commande proposé donne de la robustesse au système en boucle fermée. De plus, une nouvelle technique de vision monoculaire par ordinateur a été utilisée pour la localisation d’un drone. Les informations visuelles sont fusionnées avec les mesures inertielles du drone pour avoir une bonne estimation de sa position. Cette technique utilise l’algorithme PTAM (localisation parallèle et mapping), qui s’agit d’obtenir un nuage de points caractéristiques dans l’image par rapport à une scène qui servira comme repère. Cet algorithme n’utilise pas de cibles, de marqueurs ou de scènes bien définies. La contribution dans cette méthodologie a été de pouvoir utiliser le nuage de points disperse pour détecter possibles obstacles en face du véhicule. Avec cette information nous avons proposé un algorithme de commande pour réaliser l’évitement d’obstacles. Cette loi de commande utilise les champs de potentiel pour calculer une force de répulsion qui sera appliquée au drone. Des expériences en temps réel ont montré la bonne performance du système proposé. Les résultats antérieurs ont motivé la conception et développement d’un drone capable de réaliser en sécurité l’interaction avec les hommes et les suivre de façon autonome. Un classificateur en cascade du type Haar a été utilisé pour détecter le visage d’une personne. Une fois le visage est détecté, on utilise un filtre de Kalman (KF) pour améliorer la détection et un algorithme pour estimer la position relative du visage. Pour réguler la position du drone et la maintenir à une distance désirée du visage, on a utilisé une loi de commande linéaireThe present document addresses, theoretically and experimentally, the most relevant topics for Unmanned Aerial Vehicles (UAVs) in autonomous and semi-autonomous navigation. According with the multidisciplinary nature of the studied problems, a wide range of techniques and theories are covered in the fields of robotics, automatic control, computer science, computer vision and embedded systems, among others. As part of this thesis, two different experimental platforms were developed in order to explore and evaluate various theories and techniques of interest for autonomous navigation. The first prototype is a quadrotor specially designed for outdoor applications and was fully developed in our lab. The second testbed is composed by a non expensive commercial quadrotor kind AR. Drone, wireless connected to a ground station equipped with the Robot Operating System (ROS), and specially intended to test computer vision algorithms and automatic control strategies in an easy, fast and safe way. In addition, this work provides a study of data fusion techniques looking to enhance the UAVs pose estimation provided by commonly used sensors. Two strategies are evaluated in particular, an Extended Kalman Filter (EKF) and a Particle Filter (PF). Both estimators are adapted for the system under consideration, taking into account noisy measurements of the UAV position, velocity and orientation. Simulations show the performance of the developed algorithms while adding noise from real GPS (Global Positioning System) measurements. Safe and accurate navigation for either autonomous trajectory tracking or haptic teleoperation of quadrotors is presented as well. A second order Sliding Mode (2-SM) control algorithm is used to track trajectories while avoiding frontal collisions in autonomous flight. The time-scale separation of the translational and rotational dynamics allows us to design position controllers by giving desired references in the roll and pitch angles, which is suitable for quadrotors equipped with an internal attitude controller. The 2-SM control allows adding robustness to the closed-loop system. A Lyapunov based analysis probes the system stability. Vision algorithms are employed to estimate the pose of the vehicle using only a monocular SLAM (Simultaneous Localization and Mapping) fused with inertial measurements. Distance to potential obstacles is detected and computed using the sparse depth map from the vision algorithm. For teleoperation tests, a haptic device is employed to feedback information to the pilot about possible collisions, by exerting opposite forces. The proposed strategies are successfully tested in real-time experiments, using a low-cost commercial quadrotor. Also, conception and development of a Micro Aerial Vehicle (MAV) able to safely interact with human users by following them autonomously, is achieved in the present work. Once a face is detected by means of a Haar cascade classifier, it is tracked applying a Kalman Filter (KF), and an estimation of the relative position with respect to the face is obtained at a high rate. A linear Proportional Derivative (PD) controller regulates the UAV’s position in order to keep a constant distance to the face, employing as well the extra available information from the embedded UAV’s sensors. Several experiments were carried out through different conditions, showing good performance even under disadvantageous scenarios like outdoor flight, being robust against illumination changes, wind perturbations, image noise and the presence of several faces on the same image. Finally, this thesis deals with the problem of implementing a safe and fast transportation system using an UAV kind quadrotor with a cable suspended load. The objective consists in transporting the load from one place to another, in a fast way and with minimum swing in the cable
25
Stepanyan, Vahram. "Vision Based Guidance and Flight Control in Problems of Aerial Tracking." Diss., Virginia Tech, 2006. http://hdl.handle.net/10919/28659.
Повний текст джерелаАнотація:
The use of visual sensors in providing the necessary information for the autonomous guidance and navigation of the unmanned-air vehicles (UAV) or micro-air vehicles (MAV) applications is inspired by biological systems and is motivated first of all by the reduction of the navigational sensor cost. Also, visual sensors can be more advantageous in military operations since they are difficult to detect. However, the design of a reliable guidance, navigation and control system for aerial vehicles based only on visual information has many unsolved problems, ranging from hardware/software development to pure control-theoretical issues, which are even more complicated when applied to the tracking of maneuvering unknown targets.
This dissertation describes guidance law design and implementation algorithms for autonomous tracking of a flying target, when the information about the target's current position is obtained via a monocular camera mounted on the tracking UAV (follower). The visual information is related to the target's relative position in the follower's body frame via the target's apparent size, which is assumed to be constant, but otherwise unknown to the follower. The formulation of the relative dynamics in the inertial frame requires the knowledge of the follower's orientation angles, which are assumed to be known. No information is assumed to be available about the target's dynamics. The follower's objective is to maintain a desired relative position irrespective of the target's motion.
Two types of guidance laws are designed and implemented in the dissertation. The first one is a smooth guidance law that guarantees asymptotic tracking of a target, the velocity of which is viewed as a time-varying disturbance, the change in magnitude of which has a bounded integral. The second one is a smooth approximation of a discontinuous guidance law that guarantees bounded tracking with adjustable bounds when the target's acceleration is viewed as a bounded but otherwise unknown time-varying disturbance. In both cases, in order to meet the objective, an intelligent excitation signal is added to the reference commands.
These guidance laws are modified to accommodate measurement noise, which is inherently available when using visual sensors and image processing algorithms associated with them. They are implemented on a full scale non-linear aircraft model using conventional block backstepping technique augmented with a neural network for approximation of modeling uncertainties and atmospheric turbulence resulting from the closed-coupled flight of two aerial vehicles.Ph. D.
26
Di, Long. "Cognitive Formation Flight in Multi-Unmanned Aerial Vehicle-Based Personal Remote Sensing Systems." DigitalCommons@USU, 2011. https://digitalcommons.usu.edu/etd/985.
Повний текст джерелаАнотація:
This work introduces a design and implementation of using multiple unmanned aerial vehicles (UAVs) to achieve cooperative formation flight based on the personal remote sensing platforms developed by the author and the colleagues in the Center for Self-Organizing and Intelligent Systems (CSOIS). The main research objective is to simulate the multiple UAV system, design a multi-agent controller to achieve simulated formation flight with formation reconfiguration and real-time controller tuning functions, implement the control system on actual UAV platforms and demonstrate the control strategy and various formation scenarios in practical flight tests. Research combines analysis on flight control stabilities, develop- ment of a low-cost UAV testbed, mission planning and trajectory tracking, multiple sensor fusion research for UAV attitude estimations, low-cost inertial measurement unit (IMU) evaluation studies, AggieAir remote sensing platform and fail-safe feature development, al- titude controller design for vertical take-off and landing (VTOL) aircraft, and calibration and implementation of an air pressure sensor for wind profiling purposes on the developed multi-UAV platform. Definitions of the research topics and the plans are also addressed.
27
Masango, Thubalakhe Patrick. "Condition monitoring of a wing structure for an unmanned aerial vehicle (UAV)." Thesis, Cape Peninsula University of Technology, 2015. http://hdl.handle.net/20.500.11838/2384.
Повний текст джерелаАнотація:
Thesis (MTech (Mechanical Engineering))--Cape Peninsula University of Technology, 2015.Currently non-destructive testing techniques for composite aircraft structures are disadvantaged when compared to online Structural Health Monitoring (SHM) systems that monitor the structure while in-service and give real time data. The present research work looks at developing a protocol for online structural health monitoring of a UAV wing structure using PVDF film sensors, especially including the monitoring of structural changes caused by defects. Different types of SHM techniques were studied in relation to carbon fibre composites. Laminate composite make-up and manufacturing process was investigated and vacuum infusion process was used to manufacture the samples that resemble the Guardian II wing structure, then the three-point bending test was used to determine the material properties. Digital Shearography was employed as a stationery non-destructive technique to determine the sensor to structure attachment, type and position of defects that affect the state of performance. Finite Element Analysis (FEA) was done using ANSYS Workbench which served as a modelling tool using a drawing imported from Solid-works. Experimental investigation was done using PVDF sensor embedded on the surface of the sample in a cantilever setup and a vertical Vernier scale to measure the deflection due to impact and vibration loading. A Fluke-View oscilloscope was used as a data logger when the measurement of the output voltage and the natural frequency were recorded. The techniques of using FEA and experimental investigation were then compared. The findings of this study showed that the PVDF sensor is suitable for condition monitoring of a UAV wing structure.
28
Gonzalez, Castro Luis Nicolas. "Coherent design of uninhabited aerial vehicle operations and control stations." Thesis, Available online, Georgia Institute of Technology, 2006, 2006. http://etd.gatech.edu/theses/available/etd-05182006-172951/.
Повний текст джерела
29
Flood, Christopher H. "Design and evaluation of a digital flight control system for the Frog Unmanned Aerial Vehicle." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2001. http://handle.dtic.mil/100.2/ADA397294.
Повний текст джерелаАнотація:
Thesis (Degree of Aeronautical and Astronautical Engineer)--NavalPostgraduate School, Sept. 2001.Thesis adviso(s): Kaminer, Isaac I. "September 2001." Includes bibliographical references (p. 113). Also Available online.
30
Svanfeldt, Mårten. "Design of the hardware platform for the flight control system in an unmanned aerial vehicle." Thesis, Linköping University, Electronics System, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-58985.
Повний текст джерела
31
Brynestad, Mark A. "Investigation of the flight control requirements of a half-scale ducted fan Unmanned Aerial Vehicle." Thesis, Monterey, Calif. : Naval Postgraduate School, 1992. http://handle.dtic.mil/100.2/ADA252730.
Повний текст джерелаАнотація:
Thesis (degree of Aeronautical and Astronautical Engineer)--Naval Postgraduate School, March 1992.Thesis Advisor: Howard, Richard M. "March, 1992." Description based on title screen as viewed on March 10, 2009. Includes bibliographical references (p. 75-76). Also available in print.
32
Lim, Bock-Aeng. "Design and rapid prototyping of flight control and navigation system for an unmanned aerial vehicle." Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2002. http://sirsi.nps.navy.mil/uhtbin/hyperion-image/02Mar%5FLimBA.pdf.
Повний текст джерела
33
Marchini, Brian Decimo. "Adaptive Control Techniques for Transition-to-Hover Flight of Fixed-Wing UAVs." DigitalCommons@CalPoly, 2013. https://digitalcommons.calpoly.edu/theses/1108.
Повний текст джерелаАнотація:
Fixed-wing unmanned aerial vehicles (UAVs) with the ability to hover combine the speed and endurance of traditional fixed-wing fight with the stable hovering and vertical takeoff and landing (VTOL) capabilities of helicopters and quadrotors. This combination of abilities can provide strategic advantages for UAV operators, especially when operating in urban environments where the airspace may be crowded with obstacles. Traditionally, fixed-wing UAVs with hovering capabilities had to be custom designed for specific payloads and missions, often requiring custom autopilots and unconventional airframe configurations. With recent government spending cuts, UAV operators like the military and law enforcement agencies have been urging UAV developers to make their aircraft cheaper, more versatile, and easier to repair. This thesis discusses the use of the commercially available ArduPilot open source autopilot, to autonomously transition a fixed-wing UAV to and from hover flight. Software modifications were made to the ArduPilot firmware to add hover flight modes using both Proportional, Integral, Derivative (PID) Control and Model Reference Adaptive Control (MRAC) with the goal of making the controllers robust enough so that anyone in the ArduPilot community could use their own ArduPilot board and their own fixed-wing airframe (as long as it has enough power to maintain stable hover) to achieve autonomous hover after some simple gain tuning. Three new hover flight modes were developed and tested first in simulation and then in flight using an E-Flight Carbon Z Yak 54 RC aircraft model, which was equipped with an ArduPilot 2.5 autopilot board. Results from both the simulations and flight test experiments where the airplane transitions both to and from autonomous hover flight are presented.
34
Smit, Samuel Jacobus Adriaan. "Autonomous landing of a fixed-wing unmanned aerial vehicle using differential GPS." Thesis, Stellenbosch : Stellenbosch University, 2013. http://hdl.handle.net/10019.1/80122.
Повний текст джерелаАнотація:
Thesis (MScEng)--Stellenbosch University, 2013.ENGLISH ABSTRACT: This dissertation presents the design and practical demonstration of a flight control system (FCS) that is capable of autonomously landing a fixed-wing, unmanned aerial vehicle (UAV) on a stationary platform aided by a high-precision differential global positioning system. This project forms part of on-going research with the end goal of landing a fixed-wing UAV on a moving platform (for example a ship’s deck) in windy conditions. The main aim of this project is to be able to land the UAV autonomously, safely and accurately on the runway. To this end, an airframe was selected and equipped with an avionics payload. The equipped airframe’s stability derivatives were analysed via AVL and the moment of inertia was determined by the double pendulum method. The aircraft model was developed in such a way that the specific force and moment model (high bandwidth) is split from the point-mass dynamics of the aircraft (low bandwidth) [1]. The advantage of modelling the aircraft according to this unique method, results in a design that has simple decoupled linear controllers. The inner-loop controllers control the high-bandwidth specific accelerations and roll-rate, while the outer-loop controllers control the low-bandwidth point-mass dynamics. The performance of the developed auto-landing flight control system was tested in software-in-the-loop (SIL) and hardware-in-the-loop (HIL) simulations. A Monte Carlo non-linear landing simulation analysis showed that the FCS is expected to land the aircraft 95% of the time within a circle with a diameter of 1.5m. Practical flight tests verified the theoretical results of the developed controllers and the project was concluded with five autonomous landings. The aircraft landed within a circle with a 7.5m radius with the aiming point at the centre of the circle. In the practical landings the longitudinal landing error dominated the landing performance of the autonomous landing system. The large longitudinal error resulted from a climb rate bias on the estimated climb rate and a shallow landing glide slope.
AFRIKAANSE OPSOMMING: Hierdie skripsie stel die ontwikkeling en praktiese demonstrasie van ʼn self-landdende onbemande vastevlerkvliegtuigstelsel voor, wat op ʼn stilstaande platform te lande kan kom met behulp van ʼn uiters akkurate globale posisionering stelsel. Die projek maak deel uit van ʼn groter projek, waarvan die doel is om ʼn onbemande vastevlerkvliegtuig op ʼn bewegende platform te laat land (bv. op ʼn boot se dek) in onstuimige windtoestande. Die hoofdoel van die projek was om die vliegtuig so akkuraat as moontlik op die aanloopbaan te laat land. ʼn Vliegtuigraamwerk is vir dié doel gekies wat met gepaste avionica uitgerus is. Die uitgeruste vliegtuig se aerodinamsie eienskappe was geanaliseer met AVL en die traagheidsmoment is deur die dubbelependulum metode bepaal. Die vliegtuigmodel is op so ‘n manier onwikkel om [1] die spesifieke krag en momentmodel (vinnige reaksie) te skei van die puntmassadinamiek (stadige reaksie). Die voordeel van hierdie wyse van modulering is dat eenvoudige ontkoppelde beheerders ontwerp kon word. Die binnelusbeheerders beheer die vinnige reaksie-spesifieke versnellings en die rol tempo van die vliegtuig. Die buitelusbeheerders beheer die stadige reaksie puntmassa dinamiek. Die vliegbeheerstelsel is in sagteware-in-die-lus en hardeware-in-die-lus simulasies getoets. Die vliegtuig se landingseienskappe is ondersoek deur die uitvoer van Monte Carlo simulasies, die simulasie resultate wys dat die vliegtuig 95% van die tyd binne in ʼn sirkel met ʼn diameter van 1.5m geland het. Praktiese vlugtoetse het bevestig dat die teoretiese uitslae en die prakties uitslae ooreenstem. Die vliegtuig het twee suksesvolle outomatiese landings uitgevoer, waar dit binne ʼn 7.5m-radius sirkel geland het, waarvan die gewenste landingspunt die middelpunt was. In die outomatiese landings is die longitudinale landingsfout die grootse. Die groot longitudinale landingsfout is as gevolg van ʼn afset op die afgeskatte afwaartse spoed en ʼn lae landings gradiënt.
35
Thamann, Michael. "AERODYNAMICS AND CONTROL OF A DEPLOYABLE WING UAV FOR AUTONOMOUS FLIGHT." UKnowledge, 2012. http://uknowledge.uky.edu/me_etds/18.
Повний текст джерелаАнотація:
UAV development and usage has increased dramatically in the last 15 years. In this time frame the potential has been realized for deployable UAVs to the extent that a new class of UAV was defined for these systems. Inflatable wing UAVs provide a unique solution for deployable UAVs because they are highly packable (some collapsing to 5-10% of their deployed volume) and have the potential for the incorporation of wing shaping. In this thesis, aerodynamic coefficients and aileron effectiveness were derived from the equations of motion of aircraft as necessary parameters for autonomous flight. A wind tunnel experiment was performed to determine the aerodynamic performance of a bumpy inflatable wing airfoil for comparison with the baseline smooth airfoil from which it was derived. Results showed that the bumpy airfoil has improved aerodynamics over the smooth airfoil at low-Re. The results were also used to create aerodynamic performance curves to supplement results of aerodynamic modeling with a smooth airfoil. A modeling process was then developed to calculate the aileron effectiveness of a wing shaping demonstrator aircraft. Successful autonomous flight tests were then performed with the demonstrator aircraft including in-flight aileron doublets to validate the predicted aileron effectiveness, which matched within 8%.
36
Elmore, Joel D. "Design of an All-In-One Embedded Flight Control System." VCU Scholars Compass, 2015. http://scholarscompass.vcu.edu/etd/3981.
Повний текст джерелаАнотація:
This thesis describes an all-in-one flight control system (FCS) that was designed for unmanned aerial vehicles (UAVs). The project focuses on the embedded hardware aspect of a stand-alone system with low-cost and reliability in mind.
37
Khakimbayev, Jasur S. "Development of integrated 3D terrain maps for Unmanned Aerial Vehicle (UAV) Flight and Mission Control Support System (FMCSS)." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2006. http://library.nps.navy.mil/uhtbin/hyperion/06Mar%5FKhakimbayev.pdf.
Повний текст джерелаАнотація:
Thesis (M.S. in Modeling, Virtual Environments, and Simulation (Moves))--Naval Postgraduate School, March 2006.Thesis Advisor(s): Wolfgang Baer, Curtis L. Blais. "March 2006." Includes bibliographical references (p.99-101). Also available online.
38
Basson, Lionel. "Control allocation as part of a fault-tolerant control architecture for UAVs." Thesis, Stellenbosch : University of Stellenbosch, 2011. http://hdl.handle.net/10019.1/6722.
Повний текст джерелаАнотація:
Thesis (MScEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2011.ENGLISH ABSTRACT: The development of a control allocation system for use as part of a fault-tolerant control (FTC) system in unmanned aerial vehicles (UAVs) is presented. This system plays a vital role in minimising the possibility that a fault will necessitate the reconfiguration of the control, guidance or navigation systems of the aircraft by minimising the difference between the desired and achievable aircraft performance parameters. This is achieved by optimising the allocation of control effort commanded by the virtual actuators to the physical actuators present on the aircraft. A simple general six degree of freedom aircraft model is presented that contains all of the relevant terms needed to find the trim biases of the aircraft actuators and evaluate the performance of the virtual actuators. This model was used to develop a control allocation formulation that optimises the performance of the virtual actuators of the aircraft while minimising adverse effects and avoiding actuator saturation. The resulting problem formulation was formulated as a multi-objective optimisation problem which was solved using the sequential quadratic programming method. The control allocation system was practically implemented and tested. A number of failure categories of varying severity were defined and two aircraft with different levels of actuator redundancy were used to test the system. The control allocation algorithm was evaluated for each failure category, aircraft test case and for a number of differing control allocation system configurations. A number of enhancements were then made to the control allocation system which included adding frequency-based allocation and adapting the algorithm for an unconventional ducted-fan UAV. The control allocation system is shown to be applicable to a number of different conventional aircraft configurations with no alterations as well as being applicable to unconventional aircraft with minor alterations. The control allocation system is shown to be capable of handling both single and multiple actuator failures and the importance of actuator redundancy is highlighted as a factor that influences the effectiveness of control allocation. The control allocation system can be effectively used as part of a FTC system or as a tool that can be used to investigate control allocation and aircraft redundancy.
AFRIKAANSE OPSOMMING: Die ontwikkeling van ’n beheertoekenning sisteem vir gebruik as deel van ’n fout verdraagsame beheersisteem in onbemande lugvaartuie word voorgelê. Hierdie sisteem speel ’n essensiële rol in die vermindering van die moontlikheid dat ’n fout die herkonfigurasie van die beheer, bestuur of navigasiesisteme van die vaartuig tot gevolg sal hê, deur die verskil te verminder tussen die verlangde en bereikbare werkverrigtingsraamwerk van die vaartuig. Dit word bereik deur die optimisering van die toekenning van beheerpoging aangevoer deur die virtuele aktueerders na die fisiese aktueerders teenwoordig op die vaartuig. ’n Eenvoudige algemene ses grade van vryheid lugvaartuig model word voorgestel wat al die relevante terme bevat wat benodig word om die onewewigtigheid verstelling van die vaartuig se aktueerders te vind en die werksverrigting van die virtuele aktueerders te evalueer. Hierdie model is gebruik om ’n beheer toekenning formulering te ontwikkel wat die werkverrigting van die virtuele aktueerders van die vaartuig optimiseer terwyl nadelige gevolge verminder word asook aktueerder versadiging vermy word. Die gevolglike probleem formulering is omskryf as ’n multi-doel optimiserings probleem wat opgelos is deur gebruik van die sekwensiële kwadratiese programmerings metode. Die beheertoekenning sisteem is prakties geïmplementeer en getoets. ’n Aantal fout kategorieë van verskillende grade van erns is gedefinieer en twee vaartuie met verskillende vlakke van aktueerder oortolligheid is gebruik om die sisteem te toets. Die beheer toekenning algoritme is geëvalueer vir elke fout kategorie, vaartuig toetsgeval, asook vir ’n aantal verskillende beheertoekenning sisteem konfigurasies. ’n Aantal verbeterings is aangebring aan die beheertoekenning sisteem, naamlik die toevoeging van frekwensie gebaseerde toekenning en wysiging van die algoritme vir ’n onkonvensionele onbemande geleide waaier lugvaartuig. Die beheertoekenning sisteem is van toepassing op ’n aantal verskillende konvensionele vaartuig konfigurasies met geen verstellings asook van toepassing op onkonvensionele vaartuie met geringe verstellings. Die beheertoekenning sisteem kan beide enkel- en veelvoudige aktueerder tekortkominge hanteer en die belangrikheid van aktueerder oortolligheid is beklemtoon as ’n faktor wat die effektiwiteit van beheertoekenning beïnvloed. Die beheertoekenning sisteem kan effektief geïmplementeer word as deel van ’n fout verdraagsame beheersisteem of as ’n werktuig om beheertoekenning en vaartuig oortolligheid te ondersoek.
39
SARTORI, DANIELE. "Design, Implementation and Testing of Advanced Control Laws for Fixed-wing UAVs." Doctoral thesis, Politecnico di Torino, 2014. http://hdl.handle.net/11583/2571146.
Повний текст джерелаАнотація:
The present PhD thesis addresses the problem of the control of small fixed-wing Unmanned
Aerial Vehicles (UAVs). In the scientific community much research is dedicated to the study
of suitable control laws for this category of aircraft. This interest is motivated by the several
applications that these platforms can perform and by their peculiarities as dynamical systems.
In fact, small UAVs are characterized by highly nonlinear behavior, strong coupling between
longitudinal and latero-directional planes, and high sensitivity to external disturbances and
to parametric uncertainties. Furthermore, the challenge is increased by the limited space
and weight available for the onboard electronics. The aim of this PhD thesis is to provide a
valid confrontation among three different control techniques and to introduce an innovative
autopilot configuration suitable for the unmanned aircraft field.
Three advanced controllers for fixed-wing unmanned aircraft vehicles are designed and
implemented: PID with H1 robust approach, L1 adaptive controller and nonlinear backstepping
controller. All of them are analyzed from the theoretical point of view and validated
through numerical simulations with a mathematical UAV model. One is implemented on a
microcontroller board, validated through hardware simulations and tested in
flight.
The PID with H1 robust approach is used for the definition of the gains of a commercial
autopilot. The proposed technique combines traditional PID control with an H1 loop
shaping method to assess the robustness characteristics achievable with simple PID gains.
It is demonstrated that this hybrid approach provides a promising solution to the problem
of tuning commercial autopilots for UAVs. Nevertheless, it is clear that a tradeoff between
robustness and performance is necessary when dealing with this standard control technique.
The robustness problem is effectively solved by the adoption of an L1 adaptive controller
for complete aircraft control. In particular, the L1 logic here adopted is based on piecewise
constant adaptive laws with an adaptation rate compatible with the sampling rate of an autopilot
board CPU. The control scheme includes an L1 adaptive controller for the inner loop,
while PID gains take care of the outer loop. The global controller is tuned on a linear decoupled
aircraft model. It is demonstrated that the achieved configuration guarantees satisfying
performance also when applied to a complete nonlinear model affected by uncertainties and parametric perturbations.
The third controller implemented is based on an existing nonlinear backstepping technique.
A scheme for longitudinal and latero-directional control based on the combination of
PID for the outer loop and backstepping for the inner loop is proposed. Satisfying results are
achieved also when the nonlinear aircraft model is perturbed by parametric uncertainties. A
confrontation among the three controllers shows that L1 and backstepping are comparable
in terms of nominal and robust performance, with an advantage for L1, while the PID is
always inferior.
The backstepping controller is chosen for being implemented and tested on a real fixed-wing
RC aircraft. Hardware-in-the-loop simulations validate its real-time control capability
on the complete nonlinear model of the aircraft adopted for the tests, inclusive of sensors
noise. An innovative microcontroller technology is employed as core of the autopilot system,
it interfaces with sensors and servos in order to handle input/output operations and it
performs the control law computation. Preliminary ground tests validate the suitability of
the autopilot configuration. A limited number of flight tests is performed. Promising results
are obtained for the control of longitudinal states, while latero-directional control still needs
major improvements.
40
Holt, Ryan S. "Three Enabling Technologies for Vision-Based, Forest-Fire Perimeter Surveillance Using Multiple Unmanned Aerial Systems." BYU ScholarsArchive, 2007. https://scholarsarchive.byu.edu/etd/931.
Повний текст джерелаАнотація:
The ability to gather and process information regarding the condition of forest fires is essential to cost-effective, safe, and efficient fire fighting. Advances in sensory and autopilot technology have made miniature unmanned aerial systems (UASs) an important tool in the acquisition of information. This thesis addresses some of the challenges faced when employing UASs for forest-fire perimeter surveillance; namely, perimeter tracking, cooperative perimeter surveillance, and path planning. Solutions to the first two issues are presented and a method for understanding path planning within the context of a forest-fire environment is demonstrated. Both simulation and hardware results are provided for each solution.
41
Samal, Mahendra Engineering & Information Technology Australian Defence Force Academy UNSW. "Neural network based identification and control of an unmanned helicopter." Awarded by:University of New South Wales - Australian Defence Force Academy. Engineering & Information Technology, 2009. http://handle.unsw.edu.au/1959.4/43917.
Повний текст джерелаАнотація:
This research work provides the development of an Adaptive Flight Control System (AFCS) for autonomous hover of a Rotary-wing Unmanned Aerial Vehicle (RUAV). Due to the complex, nonlinear and time-varying dynamics of the RUAV, indirect adaptive control using the Model Predictive Control (MPC) is utilised. The performance of the MPC mainly depends on the model of the RUAV used for predicting the future behaviour. Due to the complexities associated with the RUAV dynamics, a neural network based black box identification technique is used for modelling the behaviour of the RUAV. Auto-regressive neural network architecture is developed for offline and online modelling purposes. A hybrid modelling technique that exploits the advantages of both the offline and the online models is proposed. In the hybrid modelling technique, the predictions from the offline trained model are corrected by using the error predictions from the online model at every sample time. To reduce the computational time for training the neural networks, a principal component analysis based algorithm that reduces the dimension of the input training data is also proposed. This approach is shown to reduce the computational time significantly. These identification techniques are validated in numerical simulations before flight testing in the Eagle and RMAX helicopter platforms. Using the successfully validated models of the RUAVs, Neural Network based Model Predictive Controller (NN-MPC) is developed taking into account the non-linearity of the RUAVs and constraints into consideration. The parameters of the MPC are chosen to satisfy the performance requirements imposed on the flight controller. The optimisation problem is solved numerically using nonlinear optimisation techniques. The performance of the controller is extensively validated using numerical simulation models before flight testing. The effects of actuator and sensor delays and noises along with the wind gusts are taken into account during these numerical simulations. In addition, the robustness of the controller is validated numerically for possible parameter variations. The numerical simulation results are compared with a base-line PID controller. Finally, the NN-MPCs are flight tested for height control and autonomous hover. For these, SISO as well as multiple SISO controllers are used. The flight tests are conducted in varying weather conditions to validate the utility of the control technique. The NN-MPC in conjunction with the proposed hybrid modelling technique is shown to handle additional disturbances successfully. Extensive flight test results provide justification for the use of the NN-MPC technique as a reliable technique for control of non-linear complex dynamic systems such as RUAVs.
42
Sattigeri, Ramachandra Jayant. "Adaptive Estimation and Control with Application to Vision-based Autonomous Formation Flight." Diss., Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/16272.
Повний текст джерелаАнотація:
The role of vision as an additional sensing mechanism has received a lot of attention in recent years in the context of autonomous flight applications. Modern Unmanned Aerial Vehicles (UAVs) are equipped with vision sensors because of their light-weight, low-cost characteristics and also their ability to provide a rich variety of information of the environment in which the UAVs are navigating in. The problem of vision based autonomous flight is very difficult and challenging since it requires bringing together concepts from image processing and computer vision, target tracking and state estimation, and flight guidance and control.
This thesis focuses on the adaptive state estimation, guidance and control problems involved in vision-based formation flight. Specifically, the thesis presents a composite adaptation approach to the partial state estimation of a class of nonlinear systems with unmodeled dynamics. In this approach, a linear time-varying Kalman filter is the nominal state estimator which is augmented by the output of an adaptive neural network (NN) that is trained with two error signals. The benefit of the proposed approach is in its faster and more accurate adaptation to the modeling errors over a conventional approach.
The thesis also presents two approaches to the design of adaptive guidance and control (G&C) laws for line-of-sight formation flight. In the first approach, the guidance and autopilot systems are designed separately and then combined together by assuming time-scale separation. The second approach is based on integrating the guidance and autopilot design process. The developed G&C laws using both approaches are adaptive to unmodeled leader aircraft acceleration and to own aircraft aerodynamic uncertainties.
The thesis also presents theoretical justification based on Lyapunov-like stability analysis for integrating the adaptive state estimation and adaptive G&C designs. All the developed designs are validated in nonlinear, 6DOF fixed-wing aircraft simulations.
Finally, the thesis presents a decentralized coordination strategy for vision-based multiple-aircraft formation control. In this approach, each aircraft in formation regulates range from up to two nearest neighboring aircraft while simultaneously tracking nominal desired trajectories common to all aircraft and avoiding static obstacles.
43
Cakir, Zeynep. "Development Of A Uav Testbed." Master's thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12613209/index.pdf.
Повний текст джерелаАнотація:
The development and testing for a UAV testbed to be used in academic research and undergraduate education is proposed in this thesis. Analysis on commercial off-the-shelf UAV systems and autopilots lead to the development of a custom, open-architecture and modular UAV testbed. The main focus is to support research in UAV control field and education of the undergraduate students. The integration and use of commercial-off-the-shelf avionics and air vehicle are described in detail. System performance is examined both in flight and on the ground. Results of the system tests show that the developed system is a functional UAV testbed to be used in research of different flight control algorithms.
44
Lizarraga, Mariano I. "Autonomous landing system for a UAV." Thesis, Monterey California. Naval Postgraduate School, 2004. http://hdl.handle.net/10945/1655.
Повний текст джерелаАнотація:
Approved for public release, distribution is unlimitedThis thesis is part of an ongoing research conducted at the Naval Postgraduate School to achieve the autonomous shipboard landing of Unmanned Aerial Vehicles (UAV). Two main problems are addressed in this thesis. The first is to establish communication between the UAV's ground station and the Autonomous Landing Flight Control Computer effectively. The second addresses the design and implementation of an autonomous landing controller using classical control techniques. Device drivers for the sensors and the communications protocol were developed in ANSI C. The overall system was implemented in a PC104 computer running a real-time operating system developed by The Mathworks, Inc. Computer and hardware in the loop (HIL) simulation, as well as ground test results show the feasibility of the algorithm proposed here. Flight tests are scheduled to be performed in the near future.
Lieutenant Junior Grade, Mexican Navy
45
Noonan, Andrea L. "Flight plan generation for unmanned aerial vehicles." Thesis, Manhattan, Kan. : Kansas State University, 2007. http://hdl.handle.net/2097/385.
Повний текст джерела
46
Lawrance, Nicholas R. J. "Autonomous soaring flight for unmanned aerial vehicles." Thesis, The University of Sydney, 2011. https://hdl.handle.net/2123/21912.
Повний текст джерелаАнотація:
Unmanned Aerial Vehicles (UAVs) provide unique capabilities in a range of industrial, scientific and defence applications. A small UAV could extend flight duration without requiring additional propulsive power through the use of soaring. This thesis examines the aerodynamic mechanisms of soaring flight and proposes planning and control algorithms for a UAV to autonomously sense and utilise the wind environment to extend flight duration. In order to utilise soaring a thorough understanding of the energy interaction between an aircraft and the surrounding atmosphere is required. This thesis presents a mathematical model for a gliding aircraft and examines how wind contributes to the energy change of an aircraft. Conditions for optimal energy efficiency are identified for gliding and soaring flight in linear wind shear. The proposed path planner takes advantage of the energy equations for a gliding aircraft to plan energy efficient paths over a known wind field. Previous soaring planners have focused on a single type of energy gain such as static soaring. By using the energy equations directly the planner can exploit all energy gain conditions rather than relying on specialised controllers. The planner requires an adequate estimate of the wind field to plan reliable energy gain paths. A small UAV would typically only have access to direct wind observations taken during flight. Gaussian Process (GP) regression is proposed to generate a wind map from direct wind observations. This model-free approach can account for static and dynamic wind fields and does not restrict the planner to particular types of wind structure. Maintaining an accurate map requires the planner to ensure efficient map sampling and maintain sufficient energy to continue flight. The path planning algorithm exploits the variance estimate from the GP map to identify regions of the map which require improvement. The planner assesses the aircraft’s energy state and current map to determine target regions of the wind field for further exploration or energy exploitation. Results demonstrate that this architecture is capable of generating energy-gain paths in both static and dynamic wind fields. The mapping algorithm records direct samples of the wind to generate a wind map that is used by the planning algorithm to simultaneously explore and exploit the wind field to extend flight duration without propulsive power.
47
Ostler, Jon N. "Flight Testing Small, Electric Powered Unmanned Aerial Vehicles." Diss., CLICK HERE for online access, 2006. http://contentdm.lib.byu.edu/ETD/image/etd1223.pdf.
Повний текст джерела
48
Larkan, Jessica. "Centralised control of unmanned aerial vehicles." Thesis, Larkan, Jessica (2018) Centralised control of unmanned aerial vehicles. Honours thesis, Murdoch University, 2018. https://researchrepository.murdoch.edu.au/id/eprint/44790/.
Повний текст джерелаАнотація:
This report presents the supporting research, methods, and outcome of an endeavour to develop a centralised control system using NI Labview for unmanned aerial vehicles developed by Bitcraze. It outlines the structure of the work, the product, and its capabilities and significance as a contribution to the body of knowledge surrounding drone technologies.
In order to present precedent for the project and potential avenues of work, the current literature detailing similar applications and systems are summarised. These sections highlight preferable potential design choices and constraints, which were considered before a method was devised. From this research, the approach chosen for the development of the controller is detailed. The final method chosen was that of a controller developed within NI Labview and radio transmission via the Crazyradio PA dongle. This would be used in place of Bitcraze’s controller, the Crazyflie PC Client. The positioning would utilise the TDoA algorithm for positioning in combination with the Loco Positioning System.
The background of the system topology is then given. This outlines all aspects of the system which warrant significant explanation before the underlying methodology for the controller program can be presented. One important aspect was that of creating drivers for the Crazyradio dongle. The procedure for multi-UAV communication is then described. This involved assigning each Crazyflie a unique address, so that multiplexing could be performed with a single radio transceiver. The setup of the LPS and the sequence reasoning is described, as this functionality was a large component within code design. The final two sequences chosen for drone travel are a “snake” and a “circle” formation, devised to avoid collision and crashes.
A high-level walkthrough of the Labview VI assists in understanding the process followed and the potential for development of the existing code in the future. The most noteworthy sections of the code are analysed and explained, with reference to the findings of the investigation for the original system.
The outcome of the project is presented and critically examined. This includes a summary of the capabilities of the final product, as well as an assessment of the performance. It was determined that the controller effectively satisfied the key objectives defined for the endeavour. Any aims which were not adequately fulfilled are discussed, and potential methods for their future development are detailed. The most significant unfulfilled objective was implementing functionality for logging data. Potential areas for exploration through future endeavours, such as autonomy and inter-UAV communication, would allow for more complex swarm behaviour to be explored.
The result of the project was a controller capable of communication with up to five UAVs. It was capable of flight and position control and replicated the functionality available within the original Bitcraze client. This product reinforces the worth of unmanned aerial vehicle technology in the advance of society and opens avenues for further pursuit of swarm technology applications.
49
Han, Chunyang. "Robust Control of Teleoperated Unmanned Aerial Vehicles." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-278212.
Повний текст джерелаАнотація:
In this thesis, we first use the reachability theory to develop algorithms for state predictionunder delayed state or output measurements. We next develop control strategies forcollision avoidance and trajectory tracking of UAVs based on the devised algorithms andthe model predictive control theory. Finally, simulations results for collision avoidanceand trajectory tracking problems are presented, for different communication delays,using a UAV model with 6 degrees of freedom.I denna avhandling använder vi först tillgänglighetsteorin för att utveckla algoritmerför tillståndsförutsägelse under fördröjda tillstånds- eller utgångsmätningar. Därefterutvecklar kontrollstrategier för undvikande av kollision och spårning av UAV: er baseradepå de planerade algoritmerna och modellen förutsägbar kontrollteori. Slutligenpresenteras simuleringsresultat för att undvika kollision och problem med spårningav banan, för olika kommunikationsförseningar, med en UAV-modell med 6 frihetsgrader.
50
Poyi, Gwangtim Timothy. "A novel approach to the control of quad-rotor helicopters using fuzzy-neural networks." Thesis, University of Derby, 2014. http://hdl.handle.net/10545/337911.
Повний текст джерелаАнотація:
Quad-rotor helicopters are agile aircraft which are lifted and propelled by four rotors. Unlike traditional helicopters, they do not require a tail-rotor to control yaw, but can use four smaller fixed-pitch rotors. However, without an intelligent control system it is very difficult for a human to successfully fly and manoeuvre such a vehicle. Thus, most of recent research has focused on small unmanned aerial vehicles, such that advanced embedded control systems could be developed to control these aircrafts. Vehicles of this nature are very useful when it comes to situations that require unmanned operations, for instance performing tasks in dangerous and/or inaccessible environments that could put human lives at risk. This research demonstrates a consistent way of developing a robust adaptive controller for quad-rotor helicopters, using fuzzy-neural networks; creating an intelligent system that is able to monitor and control the non-linear multi-variable flying states of the quad-rotor, enabling it to adapt to the changing environmental situations and learn from past missions. Firstly, an analytical dynamic model of the quad-rotor helicopter was developed and simulated using Matlab/Simulink software, where the behaviour of the quad-rotor helicopter was assessed due to voltage excitation. Secondly, a 3-D model with the same parameter values as that of the analytical dynamic model was developed using Solidworks software. Computational Fluid Dynamics (CFD) was then used to simulate and analyse the effects of the external disturbance on the control and performance of the quad-rotor helicopter. Verification and validation of the two models were carried out by comparing the simulation results with real flight experiment results. The need for more reliable and accurate simulation data led to the development of a neural network error compensation system, which was embedded in the simulation system to correct the minor discrepancies found between the simulation and experiment results. Data obtained from the simulations were then used to train a fuzzy-neural system, made up of a hierarchy of controllers to control the attitude and position of the quad-rotor helicopter. The success of the project was measured against the quad-rotor’s ability to adapt to wind speeds of different magnitudes and directions by re-arranging the speeds of the rotors to compensate for any disturbance. From the simulation results, the fuzzy-neural controller is sufficient to achieve attitude and position control of the quad-rotor helicopter in different weather conditions, paving way for future real time applications.