Dissertations / Theses on the topic 'Adaptive Nonlinear Controller Design'
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1
Fiorentini, Lisa. "Nonlinear Adaptive Controller Design For Air-breathing Hypersonic Vehicles." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1274986563.
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Zhao, Qingrong. "Reduced-Order Robust Adaptive Controller Design and Convergence Analysis for Uncertain SISO Linear Systems with Noisy Output Measurements." University of Cincinnati / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1194564628.
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Poon, Kai-yin Kenny, and 潘啟然. "An investigation on the application of nonlinear robust adaptive control theory in AC/DC power systems." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2007. http://hub.hku.hk/bib/B38898949.
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Nketoane, Paseka Augustinus. "Design and implementation of a nonlinear controller in PLC as a part of an adroit scada system for optimal adaptive control of the activated sludge process." Thesis, Cape Peninsula University of Technology, 2009. http://hdl.handle.net/20.500.11838/1106.
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Thesis (MTech (Electrical Engineering))--Cape Peninsula University of Technology, 2009More than 70% of the earth's surface is covered by water, only a small part of which is suitable for either human consumption or agricultural use. Due to pollution from agriculture, households and industry reaching rivers, lakes and seas it is Important for wastewater to be properly treated in order to remove harmful substances before it reaches the environment. Strict environmental and health regulations together with a demand for cost effective ways of wastewater treatment have made control technology in wastewater Treatment Plants an important priority. Dissolved oxygen (DO) is the amount of oxygen in the effluent and it plays a vital role of controlling VV\YTP. Oxygen dissolves in water through mixing water surface with the atmosphere, The dissolved oxygen concentration in the aerobic part of an activated sludge process should be sufficiently high to supply enough oxygen to the microorganisms in the sludge. an excessive high DO leads to high energy consumption and may also deteriorate the sludge quality, A high DO concentration in the internally recirculated water also makes the denitrification less efficient Hence, both for economical and process reasons, it is of interest to control the DO. The used controllers are normally linear controllers, proportional integral (PI) or proportional integral derivative (PID) ones. The work of these controllers leads to bad system performance, because, the process of dissolving oxygen into the wastewater is a nonlinear process and requires nonlinear control. The aim of the research project is to develop methods for design of linear and nonlinear controllers of the concentration of the DO in the aeration tank of the WWTP and to implement the designed controllers in the frameworks of PLC. The nonlinear linearizing controller based on a reference model and Lyapunov second method is designed. Additionally a linear controller is developed in a form of PI controller based on pole placement method to improve, the performance of the closed loop system. The resultant controller is to be on a PLC as a part of Adroit SCADA system. The developed programmes are used to control the wastewater treatment process in laboratory scale plant and can be applied as a part of SCADA software for control of the wastewater treatment plants.
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Dengler, Christian [Verfasser], Boris [Akademischer Betreuer] Lohmann, Boris [Gutachter] Lohmann, and Eyke [Gutachter] Hüllermeier. "Design of Adaptive Nonlinear Controllers using Supervised Learning / Christian Dengler ; Gutachter: Boris Lohmann, Eyke Hüllermeier ; Betreuer: Boris Lohmann." München : Universitätsbibliothek der TU München, 2021. http://d-nb.info/1233428071/34.
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Diao, Lili. "Nonlinear bounded controller design." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/MQ59374.pdf.
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Karagiannis, Dimitrios. "Nonlinear adaptive control design with applications." Thesis, Imperial College London, 2005. http://hdl.handle.net/10044/1/8320.
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Panjapornpon, Chanin Soroush Masoud. "Model-based controller design for general nonlinear processes /." Philadelphia, Pa. : Drexel University, 2005. http://dspace.library.drexel.edu/handle/1860/611.
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Ustunturk, Ahmet. "Digital Controller Design For Sampled-data Nonlinear Systems." Phd thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12614267/index.pdf.
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In this thesis, digital controller design methods for sampled-data nonlinear systems are considered. Although sampled-data nonlinear control has attracted much attention in recent years, the controller design methods for sampled-data nonlinear systems are still limited. Therefore, a range of controller design methods for sampled-data nonlinear systems are developed such as backstepping, adaptive and robust backstepping, reduced-order observer-based output feedback controller design methods based on the Euler approximate model. These controllers are designed to compensate the effects of the discrepancy between the Euler approximate model and exact discrete time model, parameter estimation error in adaptive control and observer error in output feedback control which behave as disturbance. A dual-rate control scheme is presented for output-feedback stabilization of sampled-data nonlinear systems. It is shown that the designed controllers semiglobally practically asymptotically (SPA) stabilize the closed-loop sampled-data nonlinear system. Moreover, various applications of these methods are given and their performances are analyzed with simulations.
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Skaf, Zakwan. "Reliable controller design for a class of nonlinear systems." Thesis, University of Manchester, 2011. https://www.research.manchester.ac.uk/portal/en/theses/reliable-controller-design-for-a-class-of-nonlinear-systems(a6215fa6-271a-41da-b526-a072cbab74c4).html.
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Control design for nonlinear systems remains an open problem in control theory despite the recent increase in research attention. This PhD work is motivated by this fact, addressing the constructive observer design approach, the output regulation problem, minimum entropy control, fault tolerant control (FTC), and iterative FTC for nonlinear systems.
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Sagiroglu, Serkan. "Adaptive Neural Network Applications On Missile Controller Design." Master's thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/3/12611106/index.pdf.
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In this thesis, adaptive neural network controllers are designed for a high subsonic cruise missile. Two autopilot designs are included in the study using adaptive neural networks, namely an altitude hold autopilot designed for the longitudinal channel and a directional autopilot designed for heading control. Aerodynamic coefficients are obtained using missile geometrya 5-Degree of Freedom (5-DOF) simulation model is obtained, and linearized at a single trim condition. An inverted model is used in the controller. Adaptive Neural Network (ANN) controllers namely, model inversion controllers with Sigma-Pi Neural Network, Single Hidden Layer Neural Network and Background Learning implemented Single Hidden Layer Neural Network, are deployed to cancel the modeling error and are applied for the longitudinal and directional channels of the missile. This approach simplifies the autopilot designing process by combining a controller with model inversion designed for a single flight condition with an on-line learning neural network to account for errors that are caused due to the approximate inversion. Simulations are performed both in the longitudinal and directional channels in order to demonstrate the effectiveness of the implemented control algorithms. The advantages and drawbacks of the implemented neural network based controllers are indicated.
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Ali, Zeeshan. "Transitional controller design for adaptive cruise control systems." Thesis, University of Nottingham, 2011. http://eprints.nottingham.ac.uk/11977/.
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Traffic congestion is an important reason for driver frustration which in turn is the main cause of human errors and accidents. Statistics reports have shown that over 90% of accidents are caused by human errors. Therefore, it is vital to improve vehicle controls to ensure adequate safety measures in order to decrease the number of accidents or to reduce the impact of accidents. An application of mathematical control techniques to the longitudinal dynamics of a vehicle equipped with an adaptive cruise control (ACC) system is presented. This study is carried out for the detailed understanding of a complex ACC vehicle model under critical transitional manoeuvres (TMs) in order to establish safe inter-vehicle distance with zero range-rate (relative velocity) behind a preceding vehicle. TMs are performed under the influence of internal complexities from vehicle dynamics and within constrained operation boundaries. The constrained boundaries refer to the control input, states, and collision avoidance constraints. The ACC vehicle is based on a nonlinear longitudinal model that includes vehicle inertial and powertrain dynamics. The overall system modelling includes: complex vehicle models, engine maps construction, first-order vehicle modelling, controllers modelling (upper-level and lower-level controllers for ACC vehicles). The upper-level controller computes the desired acceleration commands for the lower-lever controller which then provides the throttle/brake commands for the complex vehicle model. An important aspect of this study is to compare four control strategies: proportional-integral-derivative; sliding mode; constant-time-gap; and, model predictive control for the upper-level controller analysis using a first-order ACC vehicle model. The first-order model represents the lags in the vehicle actuators and sensor signal processing and it does not consider the dynamic effects of the vehicle’s sub-models. Furthermore, parameter analyses on the complex ACC vehicle for controller and vehicle parameters have been conducted. The comparison analysis of the four control strategies shows that model predictive control (MPC) is the most appropriate control strategy for upper-level control because it solves the optimal control problem on-line, rather than off-line, for the current states of the system using the prediction model, at the same time being able to take into account operation constraints. The analysis shows that the complex ACC vehicle can successfully execute TMs, tracking closely the desired acceleration and obeying the constraints, whereas the constraints are only applied in the MPC controller formulation. It is found that a higher length of the prediction horizon should be used for a closed acceleration tracking. The effect of engine and transmission dynamics on the MPC controller and ACC vehicle performance during the gear shifting is studied. A sensitivity analysis for MPC controller and vehicle parameters indicates that a length of the control horizon that is too high can seriously disturb the vehicle behaviour, and this disturbance can be only removed if a higher value of control input cost weighting is used. Furthermore, the analysis indicates that a mass within the range of 1400-2000 kg is suitable for the considered ACC vehicle. It is recommended that a variable headway time should be used for the spacing control between the two vehicles. It is found that the vehicle response is highly sensitive to the control input cost weighting; a lower value (less than one) can lead to a highly unstable vehicle response. It is recommended that the lower-level controller must take into account the road gradient information because the complex ACC vehicle is unable to achieve the control objectives while following on a slope. Based on the results, it is concluded that a first-order ACC vehicle model can be used for the controller design, but it is not sufficient to capture the complex vehicle dynamic response. Therefore, a complex vehicle model should be of use for the detailed ACC vehicle analysis. In this research study the first-order ACC vehicle model is used for the complex vehicle validation, whereas the complex ACC vehicle model can be used for the experimental validation in future work.
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Chen, Ming-Chao, and 陳明照. "Adaptive PID Controller Design for Nonlinear Chaotic Systems." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/01585242901577524200.
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碩士元智大學
電機工程學系
96
The subject of this thesis is to design a robust adaptive Proportional-Integral-Derivative (PID) controller to deal with an uncertainty chaotic system tracking control. In this thesis, we first use sliding mode control method to control a multi-input multi-output system. Although the sliding mode control can achieve the final control results; it is far from ideal. Thus, we design an adaptive robust PID controller to mimic an ideal controller. The control gains KP, KI, KD of PID controller are adjustable parameters which can be updated online with an adequate adaptation mechanism to optimize the previously designed sliding condition. A nearly ideal controller surely can not eliminate an approximate error, thus a supervisory controller is necessarily added as a system compensated controller to reduce the approximate error. Finally, we applied the proposed control technique to a Chua’s chaotic circuit system. From the simulation results show the satisfactory control performance.
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Lee, Zheng-Hao, and 李正皓. "Adaptive Backstepping Neural Network Controller Design for Nonlinear Systems." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/86720422859150258086.
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碩士國立臺灣師範大學
工業教育學系
97
Three control methods for nonlinear systems are proposed in this thesis. The first controller design is about a B-spline adaptive backstepping controller for affine nonlinear systems. The controller is comprised of a B-spline neural network identifier and a robust controller. The B-spline neural network identifier is the main controller and the robust controller is developed to achieve tracking performance to a desired attenuation level. B-spline neural networks have the advantage over other neural networks of local output adjustment, allowing them to more easily online estimate the system dynamics by tuning their interior parameters, including control points and knot points. To online adjust these parameters, a mean-value estimation technique is proposed to avoid the higher-order derivative problem. This problem generated by both the Taylor linearization expansion and the requirement of finding the derivatives of B-spline basis functions with respect to their parameters. The second controller design is about a B-spline adaptive backstepping controller for nonaffine nonlinear systems. The control scheme combines the backstepping design technique with mean-estimation B-spline neural networks. The mean-estimation B-spline neural networks use a mean estimation technique to develop the update laws for the design of online adaptive controllers. The third controller design is about a B-spline adaptive backstepping controller for nonaffine nonlinear systems with first order filters. The backstepping design technique suffers from on explosion of complexity as order of system increases. In order to overcome this problem, the third controller design uses first order filter at each step of the backstepping design.
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Lai, Sheng-Fu, and 賴昇甫. "Design of Adaptive Optimal Tracking Controller of Affine Nonlinear Systems." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/33060639152480505477.
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Jyun-YuLin and 林濬毓. "Design and Application of Nonlinear H∞-Adaptive-Fuzzy Composite Controller." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/72595302365811796141.
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Chan, Wei Shou, and 詹為守. "Design of Adaptive Dynamic Surface Controller for Uncertain Nonlinear Systems." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/94159983284274867810.
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碩士長庚大學
電機工程學研究所
96
This thesis mainly investigates the stabilizing controller design for nonlinear systems, where dynamic surface control is utilized for the ball and beam system and the planetary gear-type inverted pendulum (PIP). In general, based on backstepping control, the problems of tracking and stability analysis can be dealt with for nonlinear systems represented as a strict feedback formation by recursively choosing proper Lyapunov functions. However, the design complexity significantly increases with respect to high order systems. For the dynamic surfaces control, a first order low-pass filter is used such that the design complexity can be reduced. PIP, a highly coupling mechanism, needs an appropriate state variable conversion so that the dynamic surface control method can be applied. Simulation results, with the comparison of backstepping control, illustrate that dynamic surface control can provide better equilibrium responses. However, the backstepping and dynamic surface control methods are not affordable with unknown parameters. In this thesis, an adaptive dynamic surface control is proposed such that the stabilized equilibrium of PIP system with unknown parameters can be achieved.
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Kun-JhueiLi and 李坤錐. "Adaptive Neural H∞-Controller Design and it's Application on Nonlinear Systems." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/2gfg8e.
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碩士國立成功大學
系統及船舶機電工程學系碩博士班
101
A general system is usually nonlinear and contains unknown elements, such as the plant parameter variations，the system uncertainties and disturbances. These factors are likely to cause ill-effects on the system performance and result in the instability of the closed-loop system. This research presents a nonlinear adaptive-neural H∞-controller，which is designed to exclude the above uncertainties . In this thesis，the RBF (Radial Basis Function) neural network is used to estimate the uncertain nonlinear terms of the system in order to speed up the convergence of estimating errors. The H∞-control low in the proposed controller is ultilized to suppress the effect of the external disturbances on the controlled outputs. The Adaptive-neural portion of the composite controller makes the controller more efficient on the estimation of uncertain states or nonlinear uncertain terms. The nonlinear system is then examined by using the Lyapunov stability theorem to ensure the closed-loop stability. An inverted pendulum and a robot manipulator are respectively used as two examples in computer simulations. The simulation results reveal that the proposed adaptive-neural H∞-controller can track the desired performance graphically by the aid of Nichols Chart or singular value plots. Besides，in this study，the adjustable gains of the proposed controller are assigned by the pole-placement method in stead of arbitrary assignment to make sure the satisfaction of the prespecified performance. The computer simulations also attest the controller feasibility of the proposed controller on achievement of the desired performance.
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Chiu-Hsiung, Chen. "Adaptive Robust Cerebellar Model Articulation Controller Design for Uncertain Nonlinear Systems." 2007. http://www.cetd.com.tw/ec/thesisdetail.aspx?etdun=U0009-2901200723001300.
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Tzeng, Guo-Shu, and 曾國書. "ADAPTIVE SLIDING MODE CONTROLLER DESIGN FOR NONLINEAR SYSTEM WITH UNMATCHED UNCERTAINTIES." Thesis, 2001. http://ndltd.ncl.edu.tw/handle/04151913284030876291.
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碩士大同大學
電機工程研究所
89
In this thesis, a robust dynamic adaptive controller design algorithm for single-input single-output (SISO) nonlinear systems with unmatched uncertainties is provided. For many practical systems, the unmatched uncertainties are common in control practice. Further, sometimes these upper bounds of the uncertainties may not be easily obtained because of the complexity of structure of the uncertainties. Therefore the problem of controlling such systems becomes more complex, more difficult and more practical. We will propose a method to combine sliding mode with adaptation fuzzy law, approximate the upper bounds of the uncertainties. Adaptive control applies the parameter adaptive technique to robustify the parametric uncertainties for nonlinear systems with unknown parametric. They can easily overcome the parametric uncertainties. Some examples and simulation results are provided to illustrate the versatility and performance of the proposed method. Finally, the suggested controller is applied to the controlling of the Inverted pendulum system. Simulation results indicate its efficiency.
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Chang, Chih-Jung, and 張志榮. "ROBUST ADAPTIVE FUZZY CONTROLLER DESIGN FOR UNCERTAIN NONLINEAR DISCRETE-TIME SYSTEMS." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/83635501686405154847.
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碩士大同大學
電機工程學系(所)
94
Generally, the robust characteristics and the stability of the uncertain systems mostly put emphasis on the continuous-time systems. In this thesis, a discrete-time robust adaptive fuzzy control scheme is proposed for a class of uncertain nonlinear discrete-time systems. The unknown nonlinear functions of the plant are approximated by the fuzzy logic system by means of some adaptive laws. In addition, in order to compensate for approximate errors, this thesis utilizes the variable structure control (VSC) with a sector. The Lyapunov synthesis approach is used to develop the adaptive laws to adjust parameters in the system. According to Lyapunov stability theorem and variable structure control (VSC), the proposed adaptive fuzzy sliding mode controller can not only guarantee tracking error, which is between outputs and desired values, to be asymptotically in decay, but also obtain the stability of the system. Finally, some examples and simulation results are provided to illustrate the feasibility of the proposed method.
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Cheng, Ching-Lung, and 鄭景隆. "HYBRID ADAPTIVE CMAC SLIDING MODE CONTROLLER DESIGN FOR UNKNOWN NONLINEAR SYSTEM." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/24814807118210170980.
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碩士大同大學
電機工程學系(所)
93
ABSTRACT In this thesis, a new hybrid adaptive cerebeller model articulation controller (CMAC) sliding mode control system is developed for a class of unknown nonlinear systems. The hybrid adaptive CMAC sliding mode controller (HACSMC) uses the direct and indirect adaptive CMAC controllers to perform the equivalent control of sliding mode control (SMC). A weighting factor is adopted to sum together the control efforts from the direct and indirect adaptive CMAC controller. Two types of methods, sign function switching controller and CMAC switching controller are proposed to design the switching control law of SMC. In sign function switching controller, we use an estimation law to estimate the upper bound of uncertainty, and combine with sign function to design the switching control law of SMC. In CMAC switching controller, a CMAC network is employed to perform the switching control law of SMC. Furthermore, a supervisory controller is appended to the HACSMC to guarantee the states staying in the boundary layer. Therefore, if HACSMC can maintain the states within the boundary layer, supervisory controller will be idle. Otherwise, the supervisory controller starts working to pull the states back to the boundary layer. In addition, the adaptive laws of the control system are derived in the sense of Lyapunov theorem, so that the stability of the system can be guaranteed. Finally, the proposed control system is applied to inverted pendulum system and Chua’s chaotic circuit. The simulation results show that the HACSMC can not only make control system have good tracking performance and strong robustness but also have more flexibility during the design process.
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Chien, Jen-Chieh, and 簡仁傑. "Adaptive Neural Network Controller Design for Nonlinear System Using SPSA Algorithm." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/38846360724571007936.
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碩士元智大學
電機工程學系
98
In this thesis, we propose a simultaneous perturbation stochastic approximation algorithm (SPSA) based decoupled PID neural network controller for a class of decoupled nonlinear multi-input-multi-output systems. Because of the characteristic of the SPSA, we do not have to know the exact mathematical model of the system to obtain the gradient information. For practical control system, the real-time controller cannot be obtained by the traditional SPSA. To overcome this problem, we propose a novel SPSA-based real-time adaptive decoupled control scheme by using PID neural network. In addition, the update laws of parameters with adaptive optimal learning rate are proposed based on the Lyapunov stability theorem, this guarantees the stability and performance of closed-loop system. In addition, the affect of the frictional force model and uncertainty are discussed and analyzes. Finally, we extend our SPSA-based adaptive decoupled control for nonlinear discrete time systems. In experimental implementation, the propsed control is realized by DSP to demonstrate the performance and the efficiency of the proposed control method.
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Liau, Shu-Min, and 廖淑敏. "ADAPTIVE DYNAMICAL FUZZY SLIDING SLIDING MODE CONTROLLER DESIGN FOR UNCERTAIN NONLINEAR SYSTEMS." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/00193723151006649452.
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碩士大同大學
電機工程研究所
91
In this thesis, in order to alleviate the control chattering, a robust dynamical sliding mode control strategy for uncertain nonlinear systems is proposed. Firstly, based on conventional sliding mode control theory, we present design procedure of the dynamical sliding mode controller. Secondly, we apply the controller incorporated into the adaptive fuzzy control scheme so that the derived controller is robust with respect to unmodeled dynamics, disturbances and approximate errors. Therefore, a adaptive fuzzy dynamical sliding mode controller for uncertain nonlinear systems is proposed to attenuate not only the effects caused by unmodeled dynamics, disturbances and approximate errors but also the chattering of the controller. Thirdly, we also apply the adaptive fuzzy dynamical sliding mode controller for the system of which states are not available. We design the observer to the estimate the tracking error and apply proposed controller to guarantee the stability of the system. The control chattering for this complex system is still reduced. Finally, we apply the adaptive fuzzy dynamical sliding mode controller to control the Duffing forced oscillation system and computer simulations show the control chattering is reduced explicitly and the robust performance. The simulation results demonstrate and conform the theoretical results.
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Chen, Ti-Hung, and 陳帝宏. "ADAPTIVE FUZZY SLIDING MODE CONTROLLER DESIGN FOR A CLASS OF NONLINEAR UNCERTAIN SYSTEMS." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/90477432094472283788.
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博士大同大學
電機工程研究所
93
In this dissertation, some adaptive fuzzy sliding mode controller (AFSMC) schemes for a class of nonlinear uncertain systems are presented. The design procedures of AFSMC can be expressed as follows: first, construct the fuzzy models to describe the input/output behavior of the give nonlinear uncertain system. Then, based on the fuzzy model, design a fuzzy sliding mode controller (FSMC) to achieve the control objective. After that, design the adaptive laws for tuning the adjustable parameters of fuzzy model by Lyapunov synthesis approach. Many publications have shown that AFSMC is a powerful and robust control scheme. But, it exist some worth studying topics in design AFSMC, such as how to guarantee the H∞ tracking performance throughout the entire system states, how to treat the system that not all the system states are available for measurement, etc. Focusing on the above-mentioned topics, this dissertation proposes the following three control strategies: (1) the modified adaptive fuzzy sliding mode controller design (MAFSMC), (2) the H∞ tracking-based adaptive fuzzy sliding mode controller design (H∞AFSMC), and (3) the observer-based adaptive fuzzy sliding mode controller design with state variable filters (O-AFSMC). Chapter 2 first presents the modified adaptive fuzzy sliding mode controller design (MAFSMC) for a class of nonlinear uncertain systems. Conventionally, the adaptive laws of AFSMC are designed as functions of the tracking error vector. In this scheme, as the tracking error vector approach zero, the adaptive laws of AFSMC would not adjust the parameters of the fuzzy models. Hence, to compensate the modeling error, it needs relatively larger control signal for achieving the control objective. It may occur that the modeling error still exist, while the tracking error vector approaches to zero. Unlike the conventional adaptive algorithm, here, we propose the modified adaptive algorithm utilizes both the tracking error and the modeling error in its adaptive laws, such that the fuzzy model parameters would continuously update until both the tracking error and the modeling error converge to zero. Thus, the fuzzy model obtained by using the proposed MAFSMC will more accurate that of the conventional AFSMC, and the proposed MAFSMC performs better than the conventional AFSMC. Chapter 3 presents the H∞ tracking-based adaptive fuzzy sliding mode controller design (H∞AFSMC) for a class of nonlinear uncertain systems. This control strategy incorporates the H∞ tracking control scheme into AFSMC and based on the proposed Lyapunov stability criterion, guarantees the H∞ tracking performance throughout the entire system states. After that, the H∞ tracking control problem can be characterized in terms of solving an eigenvalue problem (EVP) to be efficiently solved by using convex optimization techniques. Chapter 4 presents the observer-based adaptive fuzzy sliding mode controller design with state variable filters (O-AFSMC) for a class of nonlinear uncertain systems, in which not all the states are available for measurement. Conventionally, to treat this controlled system, first, the observer is applied to estimate the tracking error vector. Then, based on the estimated tracking error, the control law is designed. Next, applying strictly- positive-real (SPR)-Lyapunov design approach, design the adaptive laws to adjust the parameters of the fuzzy model. Unlike SPR-Lyapunov design approach, we adopt a set of stable state variable filters to design the adaptive laws. That is, passing the observation error, the difference between the actual tracking error and the estimated tracking error, to a set of state variable filters, obtains a filtered observation error vector, and then, based on the filtered observation error vector, the adaptive laws are designed to adjust the adjustable parameters of the fuzzy model. Since only requiring the selected state variable filters must be stable, the proposed O-AFSMC is more easily to be realized than SPR-Lyapunov design approach. The simulation results illustrate the design procedure of the proposed control strategies and demonstrate their effectiveness.
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Shen, Kun-Ming, and 沈坤明. "ROBUST OUTPUT TRACKING CONTROLLER DESIGN OF UNCERTAIN NONLINEAR SYSTEMS VIA ADAPTIVE SLIDING MODE." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/95631755552148645676.
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碩士大同大學
電機工程研究所
90
In this thesis, we have presented the design algorithm of robust output tracking controller for a SISO nonlinear control system with higher-order and unmatched uncertainties. Based on the robust design techniques for the system with respect to modeling errors, this paper combines sliding mode control with the simple adaptive law to deal with the problem of higher-order and unmatched uncertainties, and it does not need to know the upper bounds of the uncertainties. Because higher-order and unmatched uncertainties are usually complicated in real systems, we are not easy to get their upper bounds. But we can use the simple adaptive law to estimate the upper bounds of the uncertainties. Moreover, because the sliding surface for the system causes chattering phenomenon, we use the controller with the saturation function to avoid this phenomenon. Some examples and simulation results are provided to illustrate the versatility and performance of the proposed method. Finally, the suggested controller is applied to the controlling of the Robot with Flexible Joint, and an inverted pendulum system. Simulation results indicate its efficiency.
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Wang, Shih-Wei, and 王士瑋. "DESIGN OF OBSERVER-BASED ROBUST ADAPTIVE FUZZY CONTROLLER FOR UNCERTAIN OUTPUT-DELAY NONLINEAR SYSTEMS." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/8g383q.
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碩士大同大學
電機工程學系(所)
95
In this thesis, an observer-based robust adaptive fuzzy controller is proposed to deal with the problems of asymptotic stabilization and output tracking performance for a class of uncertain single-input single-output (SISO) nonlinear systems with output delay and unmatched uncertainties. Within this scheme, the state observer is applied for estimating all states which are not available for measurement in the system, and then fuzzy logic systems and some adaptive laws are used to approximate the unknown nonlinear functions and the unknown upper bounds of unmatched uncertainties. By constructing an appropriate Lyapunov function and solving Lyapunov equations, the proposed robust adaptive fuzzy controller can guarantee that the asymptotic stabilization and the output tracking performance of the whole closed-loop system can be achieved. Finally, some simulation examples are given to illustrate the effectiveness of the proposed approach.
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Chiu, Yu-Hsiang, and 邱郁翔. "DESIGN OF THE NEURO-ADAPTIVE TERMINAL SLIDING MODE CONTROLLER FOR THE UNKNOWN NONLINEAR SYSTEMS." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/98155693504790396891.
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碩士大同大學
電機工程學系(所)
93
In this thesis, a neuro-adaptive terminal sliding mode controller (NATSMC) for unknown nonlinear dynamical systems is proposed. This controller is composed of two parts, one is an adaptive terminal sliding mode controller, which gives robust stability for system in the presence of parameter variations, uncertainties, and disturbances, and provides the property that the system state variables reach zero in finite time. The other is a neural network controller, which can estimate and simulates the unknown equivalent controller which due to the unknown dynamical system by the weight updates itself. Finally, the parameter of the adaptive terminal sliding mode controller can be tuned based on the Lyapunov stability analyzes. For compare the performance of the system in the terminal sliding mode with the performance of the system in the sliding mode, we replace the terminal sliding mode controller (TSMC) by traditional sliding mode controller(SMC) in overall controller, and apply the two controllers to control a numerical nonlinear control system and an inverted pendulum control system. The simulation results demonstrate the applicability of the proposed method, and the neuro-adaptive terminal sliding mode controller has batter system performance. Finally, according to the different parameters of the terminal sliding surface, the simulations demonstrate the different system states convergent speed and system response.
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Wen, Hsin-Min, and 温欣旻. "Adaptive Recurrent Fuzzy Cerebellar Model Articulation Controller Design for a Class of Nonlinear Systems." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/40304870540705731484.
Full textAbstract:
碩士清雲科技大學
電機工程所
101
In this thesis, an adaptive intelligent indirect control system is developed for the uncertain nonlinear systems. This proposed control system is composed of two systems. One is a backstepping control system utilized as the main controller, in which an adaptive recurrent fuzzy cerebellar model articulation controller neural network is designed to identify the dynamics of the system models. Another one is a robust controller utilized to achieve system’s robust characteristics, which is designed to attenuate the effect of the residual approximation errors and external disturbances with desired attenuation level. Moreover, the all adaptation laws of the adaptive intelligent indirect control system are derived based on the Lyapunov stability analysis, the Taylor linearization technique, backstepping control technique and control theory, so that the stability of the closed-loop system and tracking performance can be guaranteed. Finally, the proposed control system is applied to control a Duffing-Holmes chaotic system, a Genesio chaotic system, an inverted pendulum system and Chua’s chaotic system. From the simulation results, it is verified that the proposed control scheme can achieve favorable tracking performance for these nonlinear systems.
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Kuo, Chun-Wei, and 郭峻瑋. "ROBUST OUTPUT TRACKING FUZZY CONTROLLER DESIGN OF UNCERTAIN NONLINEAR SYSTEMS VIA ADAPTIVE MOVING SLIDING MODE." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/45370673274952081344.
Full textAbstract:
碩士大同大學
電機工程研究所
91
In this thesis, we have presented the design algorithm of robust output tracking fuzzy controller for a SISO nonlinear control system with higher-order and unmatched uncertainties. Because higher-order and unmatched uncertainties are usually complicated in real systems, we will introduce a method that combine the skill of sliding mode with extensive adaptation law to deal with the problem of higher-order and unmatched uncertainties without the knowledge of the upper bounds of these uncertainties. The moving sliding surface is used to improve the tracking behaviors of the variable structure control (VSCS) subjected to parameter variations and disturbances. This thesis applies fuzzy techniques to selecting the sliding surface when errors lie in the second and the fourth quadrants and shifting a predetermined sliding surface when errors lie in the first and the third quadrants in order to achieve the propose of fast and robust tracking. Moreover, because the sliding surface for the systems causes chattering phenomenon, we introduce two techniques to deal with that chattering phenomenon. One is the controller with the saturation function, the other is fuzzification of sliding surface. They will increase the ability of tolerance in system nonidentity and decrease the chattering phenomenon. Finally, several examples and simulation results are performed to illustrate the efficiency of the proposed method.
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Lee, Lian-Wang, and 李聯旺. "Adaptive Sliding Mode Controller Design of Nonlinear System and Application to Fluid Power Servo System." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/38053518949844807544.
Full textAbstract:
博士國立臺灣科技大學
自動化及控制研究所
97
This dissertation presents the theoretical and experimental study of fluid power servo system which could be classified into two different domains, pneumatic servo system and variable displacement electro-hydraulic pump-controlled servo system (VDEHPCSS). Since the fluid power servo system has nonlinear and time-varying behavior, it is difficult to establish an accurate dynamic model for a model-based sliding mode control design. To deal with this problem, this dissertation proposes several stable adaptive sliding mode controllers, some of which are then applied to the pneumatic servo system and VDEHPCSS. Therefore, this dissertation is organized into two parts: Part I develops the Fourier series-based adaptive sliding mode controller for pneumatic servo system and Part II presents the adaptive fuzzy controller with self-tuning fuzzy sliding mode compensation for VDEHPCSS. In Part I, the dominant nonlinearities in pneumatic servo systems are the couplings between motion and pressure, between pressure and flow rate, the valve nonlinearities and the cylinder friction. The nonlinear friction, especially the friction behaviour at velocity reversal, is the big obstacle for high precision motion control of a pneumatic servo system. The valve nonlinearities are complicated and it is necessary to consider their integral nonlinear effect. Thus, this study proposes a new Fourier series-based adaptive sliding mode controller with tracking performance (FSB-ASMC+ ) for pneumatic servo systems. Our controller first employs the Fourier series-based functional approximation technique to approximate the unknown nonlinear functions, thus bypassing the model-based prerequisite. Next, further efforts are made to improve the dynamic tracking performance we incorporate the tracking design technique into an adaptive sliding mode control method to make the derived controller robust against approximated errors, unmodeled dynamics and disturbances. The advantages of the proposed method are that no system dynamic models are required and the serious chattering problem can be reduced by means of the tracking design technique. To guarantee the system stability, the new laws for the coefficients of the Fourier-series functions are derived by a Lyapunov function. Generality and robustness tests are made to verify the practicality of the control strategies proposed in this dissertation. Consequently, practical experiments on the rodless pneumatic servo system are successfully implemented with different tracking profiles, which validate the proposed method. In Part II, the design method and experimental implementation of an adaptive fuzzy controller with self-tuning fuzzy sliding mode compensation (AFC-STFSMC) proposed which has on-line tuning ability for dealing with the system time-varying and nonlinear uncertain behaviors for adjusting the control rule parameters. This control strategy employs the adaptive fuzzy approximation technique to design the equivalent controller of the conventional sliding mode control. Furthermore, the fuzzy sliding mode control scheme with self-tuning ability is introduced to compensate the approximation error of the equivalent controller for improving the control performance. The proposed AFC-STFSMC scheme can design the sliding mode controller with no requirement of the system dynamic model, be free from chattering, be stable tracking control performance, and be robust to uncertainties. Moreover, the stability proof of the proposed scheme using Lyapunov method is presented. The experimental results of the positioning control and the tracking control in VDEHPCSS with different strokes and external disturbance forces show that the proposed AFC-STFSMC approach can achieve excellent control performance and robustness with regard to parameter variations and external disturbance.
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Chung, Bo-Ren, and 鍾博任. "Fuzzy Neural Network Based Adaptive Backstepping Controller Design for a Class of Nonlinear Uncertain Systems." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/60403513416677700021.
Full textAbstract:
碩士元智大學
電機工程學系
95
In this thesis, an adaptive backstepping control scheme using fuzzy neural networks, called ABCFNN, is proposed for a class of nonlinear uncertain nonaffine systems. The nonlinear nonaffine system contains of external disturbance, uncertainty, or parameters variations. Two kinds of fuzzy neural network systems (FNNs) are used to estimate the unknown system functions. According to the estimations of the FNNs, the ABCFNN control input can be chosen by backstepping design procedure such that the system output follows the desired trajectory. Based on the Lyapunov approach, the adaptive laws of FNNs’ parameters are obtained. To solve the effect of FNNs’ membership functions initialization, the back-propagation algorithm and Taylor expansion method are adopted to derive the update laws of FNNs’ parameters m, ??, and θ. Besides, the proposed ABCFNN is extended to a class of nonlinear cascade systems. Finally, the proposed ABCFNN is applied to the controlling of a CSTR system and a single-link flexible-joint robot. Simulation results are shown to demonstrate the performances of our approach.
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Ou, Yi-hung, and 歐儀鴻. "Design of Adaptive Block Backstepping Controllers for Uncertain Nonlinear Systems." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/79510393404945382321.
Full textAbstract:
碩士國立中山大學
電機工程學系研究所
98
Based on the Lypunov stability theorem, a design methodology of adaptive backstepping control is proposed in this thesis for a class of multi-input systems with matched and mismatched perturbations to solve regulation problems. The systems to be controlled contain blocks’ dynamic equations, hence virtual input controllers are firstly designed so that the state variables of first blocks are asymptotically stable if each virtual control input is equal to the state variable of next block. The control input is designed in the last block to ensure asymptotic stability for each state even if the perturbations exist. In addition, adaptive mechanisms are embedded in each virtual input function and control input, so that the upper bound of perturbations is not required to be known beforehand. Finally, a numerical example and a practical application are given for demonstrating the feasibility of the proposed control scheme. 英文摘要(keyword)：adaptive block backstepping controller, mismatched parameter uncertainty, virtual input controller, Lyapunov stability .
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Li, Shu-Mao, and 李樹茂. "DESIGN OF ADAPTIVE FUZZY INTEGRAL SLIDING MODE CONTROLLER WITH STATE VARIABLE FILTERS FOR UNCERTAIN NONLINEAR SYSTEMS." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/gyeab8.
Full textAbstract:
碩士大同大學
電機工程研究所碩士班
95
This paper proposes an adaptive fuzzy integral sliding mode controller with state variable filters for uncertain nonlinear systems that not all the states are available for measurement. To design the proposed controller, we first construct the fuzzy models to describe the input/output behavior of the nonlinear dynamic system. Next, an observer is applied to estimate the tracking error vector. Based on the observer, a fuzzy integral sliding model controller is developed for guaranteeing the tracking performance. Then, by passing the observation error vector to a set of state variable filters, a filtered observation error vector is obtained. With the filtered observation error vector, the adaptive laws for adjusting the free parameters of the fuzzy models can be designed. Finally, the stability of the overall system is analyzed based on the Lyapunov method. We apply the adaptive fuzzy integral sliding mode controller with state variable filters to control an inverted pendulum system. The simulation results demonstrate the tracking performance of the proposed controller.
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Cheng, Po-Jen, and 鄭博仁. "Observer-Based Adaptive Controller Design for a Class of Nonaffine Nonlinear Systems via Fuzzy-Neural Method." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/6z5ajp.
Full textAbstract:
碩士大同大學
電機工程學系(所)
95
In this paper, an observer-based adaptive fuzzy-neural control (AFNC) scheme is developed for the (SISO) nonaffine nonlinear systems with unknown structure of nonlinearities. Because of using a suitable observer, the proposed adaptive fuzzyneural algorithm does not require the state variables to be measurable. By parameterizing the nonaffine part of the system, the original system is simplified, and the weight update law of the fuzzy-neural controller is derived. Afterwards, we design a supervisory control to estimate the approximation error of the system. Based on Lyapunov theory, the stability of the closed-loop system can be guaranteed, and all signals involved are bounded. To demonstrate the effectiveness of the proposed method, simulation results are illustrated in this paper.
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Weng, Mao-Chung, and 翁茂鈞. "Dynamic Modeling Development of a Wind Energy Conversion System and Its Nonlinear Adaptive Feedback Controller Design." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/32201093777166287311.
Full textAbstract:
碩士長庚大學
電機工程研究所
92
This paper presents the dynamic modeling development of a wind energy conversion systems (WECS) connecting the grid. It's using Matlab/Simulink software to know the dynamic roperties during different type of wind. The system exhibited a normal operation from simulation results. Also, we design a feedback controller for the wind turbine using nonlinear and adaptive control method. Simulation results are given for verification.
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Wang, Ruei-Rung, and 汪睿榮. "OBSERVER-BASED ADAPTIVE FUZZY CONTROLLER DESIGN FOR UNKNOWN NONLINEAR SYSTEM USING ESTIMATION OF BOUNDS FOR UNCERTAINTY." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/84348671842916760029.
Full textAbstract:
碩士大同大學
電機工程學系(所)
93
In this thesis, an observer-based adaptive fuzzy control method for uncertain single-input single-output nonlinear dynamical systems with unknown nonlinearities is proposed. The unknown nonlinearities are approximated by the fuzzy logic system whose parameters can be adjusted on-line according to some adaptive laws for the purpose of controlling the output of the nonlinear system to track a given trajectory. The proposed method need not the assumption that the state variables full observability, and does also not require any priori knowledge of the upper bounds on the uncertainties including approximations errors and external disturbances. And the state variables can be estimated by designing the observer. The Lyapunov stability theory is used to guarantee a uniformly ultimately bounded for the state estimation error and tracking error as well as all other signals in the closed-loop system. Finally, the proposed method is applied to control some examples of nonlinear systems and simulation results demonstrate the effectiveness of the control scheme.
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Chang, Kai-Hsiang, and 張凱翔. "DESIGN OF ROBUST ADAPTIVE FUZZY CONTROLLER FOR UNCERTAIN NONLINEAR TIME-DELAY PLANTS WITH UNKNOWN DEAD-ZONE." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/71507931075017058739.
Full textAbstract:
碩士大同大學
電機工程學系(所)
97
A robust adaptive fuzzy control framework is proposed in this thesis for a class of uncertain nonlinear time-delay systems containing an unknown dead-zone. It is well known that dead-zone characteristics and time-delay are frequently encountered in various engineering systems such as servo control system and micro positioning systems. For many of these systems, the performance is limited by dead-zone in the actuator. Generally, the dead-zone characteristics are usually poorly known and time-variant. Moreover, the existence of time-delay is frequently a source of instability in the real systems. Hence, the problem of stability analysis of time delay nonlinear systems with a dead zone has been one of the most important topic for the control design engineer. According to some adaptive laws, the unknown nonlinear functions of the plant are approximated by the fuzzy logic system. Based on Lyapunov stability theorem, the presented robust adaptive fuzzy control framework can not only guarantee the robust stability of the overall closed-loop nonlinear time-delay system containing an unknown dead-zone in the actuator but also obtain good tracking performance as well. Eventually, some illustrative examples are given to verify the validity of the developed controller.
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Hou, T. F., and 侯天富. "The Design of Nonlinear Fuzzy-Adaptive H∞ controller and its applications on themotion control of underwater ROV." Thesis, 2000. http://ndltd.ncl.edu.tw/handle/82860054319582596352.
Full textAbstract:
碩士國立成功大學
造船及船舶機械工程學系
88
In this study, we combined the H∞ control theory with Fuzzy-Adaptive controller to improve the tracking performance of Fuzzy-Adaptive controller in nonlinear cases. The unbiased estimation of states must be satisfied for Fuzzy-Adaptive controller to attenuate the tracking asymptically without disturbance, yet it is well known that the parameters and states of nonlinear systems are unknown, and the unbiased estimation of states is impossible for Fuzzy-Adaptive controller in nonlinear cases. If then the tracking performance of Fuzzy-Adaptive controller is always poor in nonlinear cases. In order to improve the tracking performance of Fuzzy-Adaptive controller, we combined it with H∞control theory to form an intelligent robust controller which is called “Fuzzy-Adaptive H∞ controller.” The new controller makes H∞ controller more intelligent and enables Fuzzy-Adaptive controller to have a better performance. Finally, the computer simulation results reveal that the external disturbance and fuzzy approximation error on tracking error can be attenuated efficiently if the weighting factors are properly chosen. The Resulting performances are also good at positioning and orientation.
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Chen, Chu-Yi, and 陳居繄. "STATE OBSERVER-BASED ROBUST ADAPTIVE FUZZY CONTROLLER DESIGN FOR A CLASS OF UNCERTAIN NONLINEAR DISCRETE-TIME SYSTEMS." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/873qxc.
Full textAbstract:
碩士大同大學
電機工程學系(所)
95
In this thesis, the design methods of observer-based robust adaptive fuzzy control and observer-based robust adaptive fuzzy sliding mode control are proposed to deal with robust characteristics and stability analysis of nonlinear discrete-time systems with uncertainties, whose states are not available for measurement. According to some adaptive laws, the unknown nonlinear functions and the uncertainties of the plant can be approximated by fuzzy logic systems, and the compensator with a sector is used to tackle the approximate errors which are caused by the above-mentioned methods. In the light of Lyapunov stability theorem and variable structure control (VSC) theory, the proposed controllers can guarantee the stability of the overall system, and the system states can follow the desired signals. Finally, two examples and simulation results are presented to illustrate the effectiveness of the proposed methods.
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Chang, Hua-Hsiang, and 張華祥. "Adaptive Backstepping Controller Design for a Class of MIMO Nonlinear Non-affine Systems Via Recurrent Neural Networks." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/74556309236195330779.
Full textAbstract:
碩士元智大學
電機工程學系
96
This thesis proposes two adaptive backstepping controllers for a class of multi- input-multi-output nonlinear uncertain non-affine systems via output recurrent wavelet neural networks (ORWNNs). The proposed ORWNN combines the advantages of wavelet-based neural network (WNN), fuzzy neural network (FNN), and output feedback layer. Before designing the adaptive controllers, we first transform the non-affine system in non-triangular form into strict-feedback-like form. The ORWNNs are used to estimate the unknown functions for developing the adaptive backstepping controller. The proposed adaptive backstepping controller combines the concept of dynamic surface control (DSC) technique to treat the major drawback of backstepping “explosion of complexity”, called ORWNN-based improved adaptive backstepping control (IABC). Based on the Lyapunov approach, IABC guarantees that system output converges to a small neighborhood of the reference signals, i.e., the tracking errors are globally uniformly ultimately bounded (UUB). Additionally, the direct adaptive backstepping control scheme using ORWNNs is developed, called DABC. The ideal virtual controllers and actual controller are approximated by ORWNNs. The corresponding robust controller is designed to compensate the approximated error of ORWNNs controller. Finally, several simulation results including two-order and three-order MIMO non-affine system in non-triangular form, double pendulums system, inverted double pendulums on cars system, two degree of freedom helicopter (2 DOF-Helicopter) system, and multi-link robot system are shown to demonstrate the performance of our approaches.
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Lin, Kuo-Ching, and 林國清. "Design of Robust Adaptive Sliding Mode Controllers for Nonlinear Mismatched Systems." Thesis, 2000. http://ndltd.ncl.edu.tw/handle/38285632640525202574.
Full textAbstract:
碩士國立中山大學
電機工程學系研究所
88
Abstract A simple design methodology of robust adaptive sliding m de utput tracking controllers for a class of MIMO nonlinear mismatched perturbed systems is presented in this thesis.First,the derivatives of tracking error �s dynamics are estimated in order t implement the designed sliding function. Then a robust tracking controller with a perturbation estimation scheme embedded is designed by using Lyapunov stability theorem.An adaptive control e ffrt embedded in the sliding m de controller is automatically as- signed by utilizing adaptive control technique,s that the information of the upper b und of the perturbation estimation error is not required.A modi fied first rder derivative estimator which is utilized in the perturba- tion estimation process is presented.The stability f the verall controlled system is als proved.Furthermore,the desired tracking accuracy can be in general achieved by adjusting the design parameters of the prop sed controller.One example is demonstrated for sh wing the feasibility f the proposed control scheme.
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Su, Tai-Ming, and 蘇泰銘. "Design of Model Reference Adaptive Tracking Controllers for Mismatch Perturbed Nonlinear Systems with Nonlinear Inputs." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/16791391565580318054.
Full textAbstract:
碩士國立中山大學
電機工程學系研究所
92
A simple design methodology of optimal model reference adaptive control (OMRAC) scheme with perturbation estimation for solving robust tracking problems is proposed in this thesis. The plant to be controlled belongs to a class of MIMO perturbed dynamic systems with input nonlinearity and time varying delay. The proposed robust tracking controller with a perturbation estimation scheme embedded is designed by using Lyapunov stability theorem. The control scheme contains three types of controllers. The first one is a linear feedback optimal controller, which is designed under the condition that no perturbation exists. The second one is an adaptive controller, it is used for adapting the unknown upper bound of perturbation estimation error. The third one is the perturbation estimation mechanism. The property of uniformly ultimately boundness is proved under the proposed control scheme, and the effects of each design parameter on the dynamic performance is also analyzed. An example is demonstrated for showing the feasibility of the proposed control scheme.
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Lu, Kuan-Sheng, and 呂冠生. "The Design of Fuzzy Model Reference Adaptive Controller for a Class of Uncertain Nonlinear Systems with Time-Delay." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/31612428519021585262.
Full textAbstract:
碩士大同大學
電機工程學系(所)
93
In this thesis, we propose a fuzzy model reference adaptive control (FMRAC) scheme for continuous-time multiple-input-multiple-output (MIMO) nonlinear systems with time delay. The proposed FMRAC scheme uses a Takagi-Seguno (TS) fuzzy proportional-integral adaptive system to obtain fast parameters adaptation and fast convergence of the tracking error. It is shown that the stability and robustness of the control system is guaranteed in the Lyapunov sense. In this thesis, the proposed FMRAC can control the time-delay nonlinear plant through learning, provides for bounded internal, and achieves asymptotic tracking of a stable reference model, even when the plant is subject to external disturbances and parameters variations. Finally, an 2 DOF parallel robot control problems subject to uncertainties and external disturbances is simulated to demonstrate the validity of the proposed scheme.
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Wang, Chun-Chieh, and 王俊傑. "Observer-Based Fuzzy Adaptive Tracking Controller Design for Nonlinear SISO Time-Delay Systems via VSS and H∞ Approaches." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/59517578981297773840.
Full textAbstract:
碩士大同大學
電機工程學系(所)
93
In this thesis, an observer-based fuzzy adaptive VSS tracking controller design algorithm is presented for a class of nonlinear SISO delayed systems with external disturbances for achieving $H^infty$ tracking performance. A two-stage design procedure to improve disturbance attenuation ability of adaptive VSS fuzzy-based controllers is proposed where the observer design is separated from the controller design. To facilitate this concept, an observer is developed for the error dynamics and Lyapunov type stability is established under certain condition. The fuzzy approximators equipped with adaptive algorithms are introduced to learn the behaviors of the uncertain dynamics. It is shown that all the states and signals of the system are bounded and the effect of the external disturbance on the tracking error can be attenuated to any prescribed level and consequently an $H^infty$ tracking control is achieved. Finally, simulation examples by the application to control of a car-like inverted pendulum are included to confirm the validity and performance of the proposed control and observer algorithms.
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Chen, Wen-Zhe, and 陳文哲. "Design of Adaptive Sliding Mode Controllers for Nonlinear Systems with Actuator Degradation." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/tfwrc9.
Full textAbstract:
碩士國立中山大學
電機工程學系研究所
106
In this thesis a design methodology of adaptive sliding mode control with consideration of actuator faults is proposed for a class of multi-input nonlinear systems with matched and mismatched perturbations to solve state regulation problems. The sliding surface was introduced first, then the controller which can handle actuator faults was designed. Adaptive and perturbation estimation mechanisms are also embedded in the proposed control scheme, so that there is no need to know the upper bounds of perturbation and perturbation estimation errors beforehand. The proposed fault tolerant control (FTC) scheme is able to drive the controlled states to zero and stay thereafter within a finite time even if the actuator fault occurs. Finally, a numerical example and a practical application are demonstrated using computer simulation for showing the applicability of the proposed FTC scheme.
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Miwa, Hideaki. "Adaptive output feedback controllers for a class of nonlinear mechanical systems." Thesis, 2002. http://wwwlib.umi.com/cr/utexas/fullcit?p3099499.
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Cheng, Yi-Chun, and 鄭逸群. "On-Line Adaptive Multiloop PID Controller Design Based on Dynamic PLS Decoupling Structure for Linear and Nonlinear MIMO Processes." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/72022656742641823796.
Full textAbstract:
碩士中原大學
化學工程研究所
91
Abstract Controlled processes in nearly all-chemical industries frequently encounter with inherently more than one variable to be controlled. They are known as multivariable or multi-input multi-output (MIMO) processes. The control of multivariable systems is not always an easy task due to its complex and interactive nature. The goal of this paper is to identify and control MIMO processes by means of the dynamic partial least squares (PLS) model, which consists of a memoryless PLS model connected in series with linear dynamic models. Unlike traditional decoupling MIMO processes, the dynamic PLS model can decompose the MIMO process into a multiloop control system in a reduced subspace. Without the decoupler design, the optimal tuning multiloop PID controller based on the concept of general minimum variance and the constrained criteria can be directly and separately applied to each control loop under the proposed PLS modeling structure. As for the nonlinear MIMO processes, the dynamic PLS (DynPLS) model, which are obtained by the instantaneous linearized neural network model at each sampling time, can still be used to decompose the MIMO process into a multiloop control system in a reduced subspace. The proposed algorithm has the following advantages: (i) It is easy to identify DynPLS since it is not necessary to identify the MIMO system by a sequence of relay identification. (ii) The coupling effect in the MIMO system is now overcome effectively. The PLS structure can be decomposed into each pair of input and output and it selects the number of control loops based on the variation captured by each pair. (iii) Unlike the sequential tuning of the multiple control loop for the iterative design in each control loop, the adaptive tuning PID controller strategy in the SISO system can be directly and simultaneously applied to each loop of the multiloop control design in the MIMO system under the decomposed structure of PLS. This simplicity and feasibility of the scheme can easily be extended to any multiloop control strategies. Simulation case studies are provided to demonstrate the effectiveness of the control design procedures of the MIMO process.
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Chien, Chia-Wei, and 簡家葦. "Design of Adaptive Block Backstepping Controllers for Perturbed Nonlinear Systems with Input Nonlinearities." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/76020394238383876608.
Full textAbstract:
碩士國立中山大學
電機工程學系研究所
100
Based on the Lyapunov stability theorem, a design methodology of adaptive block backstepping control scheme is proposed in this thesis for a class of multi-input perturbed nonlinear systems with input nonlinearities to solve regulation problems. Fuzzy control method is utilized to estimate the unknown inverse input functions in order to facilitate the design of the proposed control scheme, so that the sector condition need not to be satisfied. According to the number of block m in the plant to be controlled, m−1 virtual input controllers are designed from the first block to the (m−1)th block. Then the proposed robust controller is designed from the last block. Adaptive mechanisms are also employed in the virtual input controllers as well as the robust controller, so that the least upper bounds of perturbations and estimation errors of inverse input functions are not required. The resultant control system is able to achieve asymptotic stability. Finally, a numerical example and a practical example are given for demonstrating the feasibility of the proposed control scheme.
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Chen, Liang-Ing, and 陳亮穎. "Design of Adaptive Block Backstepping Tracking Controllers for Nonlinear Systems with Input Constraints." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/4hxquf.
Full textAbstract:
碩士國立中山大學
電機工程學系研究所
106
Based on the Lyapunov stability theorem, a design methodology of adaptive block backstepping control with perturbation estimation scheme is proposed in this thesis for a class of a perturbed multi-input nonlinear systems with input constraints. The virtual inputs of each block of the plant to be controlled is firstly introduced, then followed by the design of control inputs. Perturbation estimator and adaptive mechanisms are employed in the proposed control scheme, so that not only the derivatives of virtual input functions do not need to be computed, but also the upper bounds of perturbations as well as perturbation estimation errors are not required to be known in advance. Furthermore, the resultant control scheme guarantees the stability of the whole controlled systems, and the tracking precision can be adjusted by tuning the design parameters. One numerical example and a practical application are illustrated for demonstrating the feasibility of the proposed control scheme.