Дисертації з теми "Predictive and Adaptive Control"
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Yoon, Tae-Woong. "Robust adaptive predictive control." Thesis, University of Oxford, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.359527.
Повний текст джерелаMeVay, Alex C. H. (Alex Craige Haviland) 1979. "Predictive comparators with adaptive control." Thesis, Massachusetts Institute of Technology, 2002. http://hdl.handle.net/1721.1/29654.
Повний текст джерелаIncludes bibliographical references (p. 72).
A linear predictor and adaptive control loop are added to a conventional comparator to greatly reduce the delay. A linear predictor feeds an estimated future signal to the comparator to compensate for the comparator's internal delay. On a cycle-by-cycle basis, an adaptive controller adjusts the comparator's bias current to null the error. Emphasis is placed on low power consumption, including the development of a linear predictor with no static power consumption. Improvements of two orders of magnitude in power-delay product are demonstrated. The adaptive comparator is ideally suited for applications such as synchronous rectification but will also find broad applicability anywhere an asynchronous comparator is required, such as sensor interfaces, oscilloscope triggers, and some types of analog-digital converters.
by Alex C.H. MeVay.
M.Eng.
Brodie, K. A. "Inferential predictive control." Thesis, University of Newcastle Upon Tyne, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.310173.
Повний текст джерелаElshafei, Abdel-Latif. "Adaptive predictive control : analysis and expert implementation." Thesis, University of British Columbia, 1991. http://hdl.handle.net/2429/30802.
Повний текст джерелаApplied Science, Faculty of
Electrical and Computer Engineering, Department of
Graduate
Fun, Wey. "Adaptive motor control using predictive neural networks." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/31065.
Повний текст джерелаEure, Kenneth W. II. "Adaptive Predictive Feedback Techniques for Vibration Control." Diss., Virginia Tech, 1998. http://hdl.handle.net/10919/30342.
Повний текст джерелаPh. D.
Sheth, Katha Janak. "Model predictive control for adaptive digital human modeling." Thesis, University of Iowa, 2010. https://ir.uiowa.edu/etd/884.
Повний текст джерелаPeng, Youbin. "On adaptive control :Pole-zero placement control and generalized predictive control." Doctoral thesis, Universite Libre de Bruxelles, 1991. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/213050.
Повний текст джерелаLambert, Martin Richard. "Adaptive control of flexible systems." Thesis, University of Oxford, 1987. http://ora.ox.ac.uk/objects/uuid:d19d44f9-b7db-4b00-95be-4cf897450836.
Повний текст джерелаBrugnolli, Mateus Mussi. "Predictive adaptive cruise control in an embedded environment." Universidade de São Paulo, 2018. http://www.teses.usp.br/teses/disponiveis/3/3139/tde-24092018-151311/.
Повний текст джерелаA inclusão de sistemas avançados para assistência de direção (ADAS) tem beneficiado o conforto e segurança através da aplicação de diversas teorias de controle. Um destes sistemas é o Sistema de Controle de Cruzeiro Adaptativo. Neste trabalho, é usado uma distribuição de duas malhas de controle para uma implementação embarcada em um carro de um Controle de Cruzeiro Adaptativo. O modelo do veículo foi estimado usando a teoria de identificação de sistemas. O controle da malha externa utiliza dados de um radar para calcular uma velocidade de cruzeiro apropriada, enquanto o controle da malha interna busca o acionamento do veículo para atingir a velocidade de cruzeiro com um desempenho desejado. Para a malha interna, é utilizado duas abordagens do controle preditivo baseado em modelo: um controle com horizonte de predição finito, e um controle com horizonte de predição infinito, conhecido como IHMPC. Ambos controladores foram embarcados em um microcontrolador capaz de comunicar diretamente com a unidade eletrônica do veículo. Este trabalho valida estes controladores através de simulações com sistemas variantes e experimentos práticos com o auxílio de um dinamômetro. Ambos controladores preditivos apresentaram desempenho satisfatório, fornecendo segurança para os passageiros.
Lopez, Brett Thomas. "Adaptive robust model predictive control for nonlinear systems." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/122395.
Повний текст джерелаCataloged from PDF version of thesis.
Includes bibliographical references (pages 115-124).
Modeling error and external disturbances can severely degrade the performance of Model Predictive Control (MPC) in real-world scenarios. Robust MPC (RMPC) addresses this limitation by optimizing over control policies but at the expense of computational complexity. An alternative strategy, known as tube MPC, uses a robust controller (designed offline) to keep the system in an invariant tube centered around a desired nominal trajectory (generated online). While tube MPC regains tractability, there are several theoretical and practical problems that must be solved for it to be used in real-world scenarios. First, the decoupled trajectory and control design is inherently suboptimal, especially for systems with changing objectives or operating conditions. Second, no existing tube MPC framework is able to capture state-dependent uncertainty due to the complexity of calculating invariant tubes, resulting in overly-conservative approximations. And third, the inability to reduce state-dependent uncertainty through online parameter adaptation/estimation leads to systematic error in the trajectory design. This thesis aims to address these limitations by developing a computationally tractable nonlinear tube MPC framework that is applicable to a broad class of nonlinear systems.
"This work was supported by the National Science Foundation Graduate Research Fellowship under Grant No. 1122374, by the DARPA Fast Lightweight Autonomy (FLA) program, by the NASA Convergent Aeronautics Solutions project Design Environment for Novel Vertical Lift Vehicles (DELIVER), and by ARL DCIST under Cooperative Agreement Number W911NF- 17-2-0181"--Page 7.
by Brett T. Lopez.
Ph. D.
Ph.D. Massachusetts Institute of Technology, Department of Aeronautics and Astronautics
Morinelly, Sanchez Juan Eduardo. "Adaptive Model Predictive Control with Generalized Orthonormal Basis Functions." Research Showcase @ CMU, 2017. http://repository.cmu.edu/dissertations/1091.
Повний текст джерелаGrenholm, Sven. "Adaptive Model Predictive Control for Reference Tracking Vehicle Motion." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-286337.
Повний текст джерелаDetta examensarbete presenterar ett antal styralgoritmer för referensföljande endimensionell fordonsrörelse. En fysisk modell för ett fordons rörelsedynamik presenteras längs en förbestämd bana. Utifrån denna modell härleds en diskretiserad linjariserad prediktionsmodell. Denna prediktionsmodell används för att formulera ett K vadratiskt Programmerings-problem. Detta optimeringsproblem står till grund för en model-prediktiv regleralgoritm. Detta reglersystem augumenteras med en rekursiv minsta-kvadrat-fels algoritm för systemidentifiering, som används till att upprepande återuppskatta massan för att hantera systematiska fel i prediktionsmodellen. Dessa algoritmer används till referensföljning i position och hastighet. Utvärderingen av algoritmerna genomförs i simulation. De presenterade algoritmerna uppvisas att vara generellt sett träffsäkra och robusta. Specifika problematiska fall där prestandan blir sämre lyfts upp och förslag på hur dessa scenarion skulle kunna hanteras medföljer.
Andina, Elisa. "Complexity and Conservatism in Linear Robust Adaptive Model Predictive Control." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019.
Знайти повний текст джерелаWang, Shensheng. "Weighting normalization in optimal predictive control /." free to MU campus, to others for purchase, 2001. http://wwwlib.umi.com/cr/mo/fullcit?p3025659.
Повний текст джерелаCoca, Diana Simona. "Adaptive generalised predictive control applied to low-flow inhalational anaesthesia." Thesis, University of Sheffield, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.401186.
Повний текст джерелаRyan, Timothy Patrick. "Model Predictive Adaptive Cruise Control with Consideration of Comfort and Energy Savings." Thesis, Virginia Tech, 2021. http://hdl.handle.net/10919/103744.
Повний текст джерелаMaster of Science
The Hybrid Electric Vehicle Team (HEVT) of Virginia Tech is partaking in the 4-Year EcoCar Mobility Challenge organized by Argonne National Labs. The objective of this competition is to modify a stock 2019 Chevrolet Blazer into a hybrid. This modification is accomplished by creating a vehicle that burns less gasoline and increases customer appeal. The general target market of hybrids is smaller vehicles. As a midsize sport utility vehicle (SUV), the Blazer offers a larger vehicle with the perk of better fuel economy. In the competition, the vehicle is assessed on the ability to integrate advanced technology, improve consumer appeal, and provide comfort for the passenger. The research of this paper is centered around the design of Adaptive Cruise Control (ACC). Initially, research is conducted on various control strategies that provide the necessary functionality. A controller that predicts future events is selected for the Adaptive Cruise Control. The main objective of this research is the implementation of Adaptive Cruise Control features that provide comfort and energy consumption savings to the rider while maintaining safety as the priority. Rider comfort is achieved by creating a smoother ride. Lastly, a proper energy analysis showcases the potential energy savings with the implementation of the Adaptive Cruise Control system. The scope of this paper expands on current knowledge of Adaptive Cruise Control by using a simplified vehicle model to simulate different conditions. The city simulations of a traditional ACC system show a 14% reduction in energy at the wheel. City simulations of the environmentally friendly Adaptive Cruise Controller show a 29% reduction in energy. Both of these simulations allow for comfortable ride. Specifically, maximum car jerk is reduced by 90%. The main objective of this analysis is to demonstrate that with proper implementation, this ACC system effectively reduces energy consumption at the wheel while improving rider comfort.
Lambert, E. P. "Process control applications of long-range prediction." Thesis, University of Oxford, 1987. http://ora.ox.ac.uk/objects/uuid:de56df0b-466c-42ce-a03b-72228ad6af2a.
Повний текст джерелаMartínez, Iván García. "Indirect adaptive predictive control applied to an industrial tank level plant." Instituto Tecnológico de Aeronáutica, 2011. http://www.bd.bibl.ita.br/tde_busca/arquivo.php?codArquivo=1550.
Повний текст джерелаHernandez, Vicente Bernardo Andres. "Model predictive control for linear systems : adaptive, distributed and switching implementations." Thesis, University of Sheffield, 2018. http://etheses.whiterose.ac.uk/22174/.
Повний текст джерелаAjibulu, Ayodeji Opeoluwa. "Robust adaptive model predictive control for intelligent drinking water distribution systems." Thesis, University of Birmingham, 2018. http://etheses.bham.ac.uk//id/eprint/8193/.
Повний текст джерелаHu, Jian-Quan. "Adaptive fuzzy predictive control using a neuro-fuzzy model with application to sintering." Thesis, University of Sheffield, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.265575.
Повний текст джерелаCho, Sukhwan. "A Learning Control, Intervention Strategy for Location-Aware Adaptive Vehicle Dynamics Systems." Diss., Virginia Tech, 2015. http://hdl.handle.net/10919/74422.
Повний текст джерелаPh. D.
Lloyd, John William. "Generalized Predictive Control Parameter Adaptation Using a Fuzzy Logic Approach." Diss., Virginia Tech, 2011. http://hdl.handle.net/10919/29306.
Повний текст джерелаPh. D.
Terry, Jonathan Spencer. "Adaptive Control for Inflatable Soft Robotic Manipulators with Unknown Payloads." BYU ScholarsArchive, 2018. https://scholarsarchive.byu.edu/etd/6769.
Повний текст джерелаCastillo, Carlos L. "Fault-tolerant adaptive model predictive control using joint kalman filter for small-scale helicopter." [Tampa, Fla] : University of South Florida, 2008. http://purl.fcla.edu/usf/dc/et/SFE0002711.
Повний текст джерелаCho, B. "Control of a hybrid electric vehicle with predictive journey estimation." Thesis, Cranfield University, 2008. http://hdl.handle.net/1826/2589.
Повний текст джерелаKhariwal, Vivek. "Adaptive control of real-time media applications in best-effort networks." Texas A&M University, 2004. http://hdl.handle.net/1969.1/1236.
Повний текст джерелаAbraham, Etimbuk. "Adaptive supervisory control scheme for voltage controlled demand response in power systems." Thesis, University of Manchester, 2018. https://www.research.manchester.ac.uk/portal/en/theses/adaptive-supervisory-control-scheme-for-voltage-controlled-demand-response-in-power-systems(3e64537d-52c7-4eb5-87f2-b73fe920b9cb).html.
Повний текст джерелаShamsudin, Syariful Syafiq. "The Development of Neural Network Based System Identification and Adaptive Flight Control for an AutonomousHelicopter System." Thesis, University of Canterbury. Mechanical Engineering Department, 2013. http://hdl.handle.net/10092/8803.
Повний текст джерелаISAIA, FRANCESCO. "Exploiting the potential of adaptive building components by means of innovative control strategies." Doctoral thesis, Politecnico di Torino, 2020. http://hdl.handle.net/11583/2841166.
Повний текст джерелаSchenck, Wolfram. "Adaptive internal models for motor control and visual prediction." Berlin Logos-Verl, 2008. http://d-nb.info/989979113/04.
Повний текст джерелаLin, Xiaohai [Verfasser]. "Robust and Stochastic Model Predictive Control of Linear Systems with Predictable Additive Disturbance : with Application to Multi-Objective Adaptive Cruise Control / Xiaohai Lin." Düren : Shaker, 2020. http://d-nb.info/121347261X/34.
Повний текст джерелаPaula, Neander Alessandro da Silva. "MPC adaptativo - multimodelos para controle de sistemas não-lineares." Universidade de São Paulo, 2009. http://www.teses.usp.br/teses/disponiveis/3/3137/tde-14052009-000836/.
Повний текст джерелаDuring the operation of a MPC, the plant can change the operation point mainly due to management decision or due to the presence of measured or unmeasured disturbances. Thus, the model of the controller must be adapted to improve the control in the new operation conditions. In such a way, a better control policy can be achieved if a large number of models are identified at the possible operation points and it is available an adaptive controller that is capable of selecting the best model. In this work is presented a methodology of adaptive control with on-line identification of the most adequate model which belongs to a set of models previously obtained. The proposed methodology considers a two-layer controller and process excitation by a GBN signal in the LP optimization layer with the controller in closed loop mode. It is also presented the adaptive controller validation by comparing the proposed approach with two different techniques - MMPC and ARX Identification, to confirm the good results with this new methodology to the adaptive controller.
Li, Hancao. "Modeling and control of a pressure-limited respirator and lung mechanics." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/47667.
Повний текст джерелаWirsching, Leonard [Verfasser], and Hans Georg [Akademischer Betreuer] Bock. "Multi-Level Iteration Schemes with Adaptive Level Choice for Nonlinear Model Predictive Control / Leonard Wirsching ; Betreuer: Hans Georg Bock." Heidelberg : Universitätsbibliothek Heidelberg, 2018. http://d-nb.info/1177251639/34.
Повний текст джерелаChow, Andy Ho Fai. "Adaptive traffic control system : a study of strategies, computational speed and effect of prediction error /." View Abstract or Full-Text, 2002. http://library.ust.hk/cgi/db/thesis.pl?CIVL%202002%20CHOW.
Повний текст джерелаIncludes bibliographical references (leaves 126-129). Also available in electronic version. Access restricted to campus users.
Tang, Meng. "The Adaptive Intelligent Model for Process Diagnosis, Prediction and Control." Doctoral thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for produksjons- og kvalitetsteknikk, 2004. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-328.
Повний текст джерелаGonçalves, Diogo Antunes. "Energy management systems based on adaptive surrogate modelling." Doctoral thesis, Universidade de Aveiro, 2017. http://hdl.handle.net/10773/23559.
Повний текст джерелаEstima-se que o sector dos edifícios seja responsável por cerca de 40% da totalidade de energia consumida na União Europeia e Estados Unidos da América. 50% dessa energia está alocada a sistemas de aquecimento, ventilação e ar-condicionado (AVAC), dos quais 20% estimam-se ser desperdiçados devido a ineficiência na gestão de energia. Considera-se pertinente focar-se no melhoramento da eficiência energética do edificado, reduzindo o desperdício de forma a evitar a escassez de recursos fósseis, bem como para mitigar os problemas ambientais e as alterações climáticas causadas pelo consumo e produção de energia. A tese propõe abordagens e metodologias que permitem tomar o controlo preditivo de supervisão dos sistemas de climatização enquanto medida de reabilitação energética na requalificação de edifícios. A principal contribuição deste trabalho prende-se com a implementação e desenvolvimento de metamodelos adaptativos baseados em aprendizagem computacional que assistam o processo de otimização multi-objetivo inerente ao controlo supervisor da gestão de energia em edifícios de serviços. Esta metodologia deverá ainda permitir a sua implementação de forma agnóstica a natureza dos sistemas AVAC existentes no edifício. A metodologia apresentada propõe uma abordagem convergente com o estado da arte no desenvolvimento científico na área da inteligência artificial. O esforço mínimo requerido para a implementação deste tipo de sistema de gestão inteligente e avaliado, concluindo-se que o seu potencial de aplicação e significativo. Para este fim, foi desenvolvida uma aplicação informática capaz de conduzir toda a metodologia em regime de simulação computacional de modo a averiguar a utilidade das soluções propostas pelo sistema de controlo supervisor desenvolvido. Os resultados obtidos apresentam soluções compatíveis com o melhoramento do paradigma energético-ambiental corrente, contribuindo desse modo para uma maior sustentabilidade do edificado obsoleto em termos energéticos. Os custos com energia alocada a sistemas AVAC podem alcançar uma redução de 27% dos custos base, acompanhando uma melhoria ao nível do conforto dos ocupantes. Mesmo em casos em que a requalificação da envolvente do edifício e do sistema de climatização seja anterior a implementação de um sistema de gestão inteligente, ou que a envolvente seja já competente em termos de eficiência energética (como o caso de estudo apresentado), a poupança energética e, ainda assim, assegurada devido a natureza flexível e autodidata do sistema de supervisão proposto. Portanto, recomenda-se que a reabilitação energética de edifícios tome como prioridade a requalificação do sistema de controlo AVAC por sistemas avançados e supervisores de controlo de forma a potenciarem a inércia dos edifícios, bem como toda a informação disponível na atual era digital.
Buildings account for almost 40% of the total energy consumption in the European Union and the United States combined. From that fraction, 50% is allocated to the heating, ventilation and air-conditioning systems (HVAC), from which 20% is wasted due to system's ine ciency. Considering that most of this energy is obtained from scarce fossil reserves and its consumption has an adverse impact on the climate change problem, it is of utmost importance to reduce energy wastes, namely by improving the overall energy e ciency of buildings. This thesis postulates the implementation of intelligent supervisory control systems for new or existing HVAC equipment as an energy retro tting measure concurrent with conventional architectural and systems retro tting. The proposed methodology is characterized by a exible, yet robust predictive control algorithm, capable of supervising generic HVAC systems in real-time by suggesting high-level controls, resulting in an optimized compromise between occupants' comfort requirements and energy consumption (and/or cost), taking advantage of the building constructive characteristics and information availability. The proposed solution integrates the exibility of machine learning techniques with the robustness of surrogate models to deliver data-driven predictive models capable of assisting the multi-objective optimization problem of minimizing energy consumption and cost while improving occupants comfort. The proposed modelling and optimization strategies are presented as a novelty capable of answering the quest for a robust yet exible supervisory predictive control for generic HVAC systems. A software package capable of delivering advanced and generic supervisory predictive controls, especially focusing on the scope of building energy retro tting was developed and used as the delivery method for the results presented in this thesis. The obtained results suggest that o ce buildings, characterized by a contemporary construction and HVAC system, can be improved regarding overall energy e ciency and occupants comfort by retro tting the control solution adding a supervisory predictive control level, external to the existing HVAC system. The expected energy saving by considering the proposed control are in line with the requirements imposed by the present energy and climate change framework, with up to 27% savings of energy related costs due to autonomous demand shifting. Moreover, it is recommended that building energy retro ts should consider as a priority the update of the energy control strategies by adding supervisory solutions capable of capitalizing the use of the building thermal inertia as well as the available data in this current information era (occupancy schedules, weather, etc.).
GODBOLE, AMIT ARUN. "ADAPTIVE IMPROVEMENT OF CLIMB PERFORMANCE." University of Cincinnati / OhioLINK, 2003. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1061303791.
Повний текст джерелаAnnamalai, Andy S. K. "An adaptive autopilot design for an uninhabited surface vehicle." Thesis, University of Plymouth, 2014. http://hdl.handle.net/10026.1/3100.
Повний текст джерелаShui, Yuhao. "Strategic Trajectory Planning of Highway Lane Change Maneuver with Longitudinal Speed Control." The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1431093441.
Повний текст джерелаBRANDI, SILVIO. "Deep Reinforcement Learning-based Control Strategies for Enhancing Energy Management in HVAC Systems." Doctoral thesis, Politecnico di Torino, 2022. http://hdl.handle.net/11583/2971112.
Повний текст джерелаD'Angio, Paul Christopher. "Adaptive and Passive Non-Visual Driver Assistance Technologies for the Blind Driver Challenge®." Diss., Virginia Tech, 2012. http://hdl.handle.net/10919/27582.
Повний текст джерелаPh. D.
Nguyen, Minh Tri. "Commande adaptative multivariable avec contraintes." Grenoble INPG, 1989. http://www.theses.fr/1989INPG0100.
Повний текст джерелаÅfeldt, Tom. "Adaptive Steering Behaviour for Heavy Duty Vehicles." Thesis, KTH, Reglerteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-215134.
Повний текст джерелаIdag används till största del regelbaserade reglersystem förförarassistanssystem i lastbilar. Men lastbilschaufförer vill ha någotmer personligt och flexibelt, som kan styra lastbilen på ett mänskligtsätt med förarens egna preferenser. Maskininlärning och artificiell intelligenskan hjälpa till för att uppnå detta mål. I denna studie användsartificiella neurala nätverk för att modellera förarens styrbeteende genomScania Lane Keeping Assist. Med användning av detta modellerasförarens preferenser med avseende på placering på vägbanan och momentpåslag på ratten. En modell prediktiv kontroller kan användas föratt begränsa tillstånd och för att väga de två modellerade preferensernamot varann. Eftersom det var mycket svårt att ta fram den internaprocessmodellen som krävdes för regulatorn används istället en variantav en PI-kontroller för att styra lastbilen. De artificiella neuralanätverken kan också tillåtas att lära sig under körning för att anpassasig till förarens preferenser över tid.
Koessler, Adrien. "Contribution à l'agrandissement de l'espace de travail opérationnel des robots parallèles. Vérification du changement de mode d'assemblage et commande pour la traversée des singularités." Thesis, Université Clermont Auvergne (2017-2020), 2018. http://www.theses.fr/2018CLFAC075/document.
Повний текст джерелаCompared to their serial counterparts, parallel robots have the edge in terms of rigidity,cycle time and positioning precision. However, the reduced size of their operationalworkspace is a drawback that limits their use in the industry. Kinematic analysis explainshow the workspace is divided in aspects, separated from each others by so-called Type 2singularities. Among existing solutions for workspace enlargement, which are evaluatedin this thesis, we chose to work on a method based on singularity crossing. This can beachieved thanks to dedicated trajectory generators and control strategies. Yet, failuresin crossing can still happen and crossing success cannot be certified.In consequence, the first part of the thesis consists in the development of an algorithmable to state on the results of a crossing attempt. Such a tool does not exist inthe literature, since solvers for the forward kinematics of parallel robots diverge aroundsingularities. Nonetheless, interval methods allow to bypass this problem by trackingend-effector velocity alongside with its pose. The ability of the algorithm to detect assemblymode change is proven in simulation, and its usefulness for reliable trajectoryplanning is shown.In a second part, we seek to improve trajectory tracking through the use of advancedcontrol techniques. A review on those techniques showed adaptive control and predictivecontrol methods to be well-fitted to our application. Linear synthesis of articularadaptive control is proposed and then derived in order to predict dynamic parametersthanks to the Predictive Functional Control method. Efficiency of the proposed controllaws is evaluated in simulation.1In order to validate both contributions, algorithms and control laws are implementedon a 2-degree of freedom planar parallel robot named DexTAR. As it is mandatory forassembly mode detection, the kinematic calibration of the robot is completed from whichcertified geometric parameters are derived. Assembly mode detection is performed onreal trajectories and results are compared to those obtained in simulation. Moreover,adaptive and predictive control laws are tested in realistic cases of singularity crossingand object manipulation.Overall, proposed contributions answer the problems that were stated previously andform an improvement to the workspace enlargement method based on Type 2 singularitycrossing
Vale, Valentina Alessandra Carvalho do. "Controle de posição de um robô cartesiano por meio de técnicas adaptativas." Universidade Federal da Paraíba, 2011. http://tede.biblioteca.ufpb.br:8080/handle/tede/5311.
Повний текст джерелаCoordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES
This paper presents a design of a predictive adaptive controller and a hybrid controller for a electro pneumatic manipulator robot with three Cartesian degrees of freedom (3 DOF). The manipulator robot is composed by three electro-pneumatic valves and pneumatic cylinders for three, two with 500mm forming the XZ axis and a 400mm on the vertical axis Y. The cylinders are driven by three electro-pneumatic proportional valves controlled by computer, which directs the flow of compressed air as the needed position. Attached to the rods of each cylinder, there are scales for potentiometric measurement of their respective positions. Through two acquisition boards, electro-pneumatic valves and potentiometric scales are connected to the computer and the data is processed using the software LabVIEW® and MATLAB®. The controllers are developed through explicit models of the electropneumatic manipulator robot estimated in real time by Recursive Least Squares Algorithm (RLS).
Neste trabalho apresentam-se projetos de um controlador adaptativo preditivo e de um híbrido para um robô manipulador eletropneumático de três graus de liberdade (3 GDL) cartesiano. O robô manipulador é composto basicamente por três válvulas eletropneumáticas e por três cilindros pneumáticos, dois de 500mm formando o plano XZ e um de 400mm no eixo vertical Y. Os cilindros são acionados através de três válvulas eletropneumáticas proporcionais comandadas por computador, que direcionam o fluxo de ar comprimido conforme a necessidade de posicionamento. Acopladas às hastes de cada cilindro, estão réguas potenciométricas para medição de suas respectivas posições. Através de duas placas de aquisição, as válvulas eletropneumáticas e as réguas potenciométricas são conectadas ao computador e os dados são processados utilizando os softwares LabVIEW® e Matlab®. Os controladores são desenvolvidos através de modelos explícitos do robô manipulador eletropneumático estimados em tempo real pelo Algoritmo dos Mínimos Quadrados Recursivo (MQR).
Wilkerson, Jaxon. "Handoff of Advanced Driver Assistance Systems (ADAS) using a Driver-in-the-Loop Simulator and Model Predictive Control (MPC)." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1595262540712316.
Повний текст джерелаCavalcanti, Anderson Luiz de Oliveira. "Estudo e implementa??o de um controlador preditivo generalizado bilinear compensado adaptativo." Universidade Federal do Rio Grande do Norte, 2003. http://repositorio.ufrn.br:8080/jspui/handle/123456789/15425.
Повний текст джерелаThe present work presents the study and implementation of an adaptive bilinear compensated generalized predictive controller. This work uses conventional techniques of predictive control and includes techniques of adaptive control for better results. In order to solve control problems frequently found in the chemical industry, bilinear models are considered to represent the dynamics of the studied systems. Bilinear models are simpler than general nonlinear model, however it can to represent the intrinsic not-linearities of industrial processes. The linearization of the model, by the approach to time step quasilinear , is used to allow the application of the equations of the generalized predictive controller (GPC). Such linearization, however, generates an error of prediction, which is minimized through a compensation term. The term in study is implemented in an adaptive form, due to the nonlinear relationship between the input signal and the prediction error.Simulation results show the efficiency of adaptive predictive bilinear controller in comparison with the conventional.
O presente trabalho tem como objetivo o estudo e a implementa??o de um controlador preditivo generalizado bilinear adaptativamente compensado. Este trabalho utiliza t?cnicas de controle preditivo convencionais juntamente com t?cnicas de controle adaptativo na busca de um melhor resultado. No intuito de solucionar problemas de controle freq?entemente enfrentados pela ind?stria qu?mica, ? proposto o modelo bilinear para representar a din?mica dos sistemas em estudo. Os modelos bilineares s?o uma classe particular dentre os modelos n?o-lineares, por?m s?o por natureza mais simples que os modelos n?o lineares gerais e ainda conseguem representar as n?o-linearidades intr?nsecas dos processos industriais. A lineariza??o do modelo, pela aproxima??o quasilinear por degrau de tempo, ? utilizada para viabilizar a aplica??o das equa??es do controlador preditivo generalizado (GPC). Tal lineariza??o, no entanto, gera um erro de predi??o, o qual ? minimizado atrav?s de um termo de compensa??o. O termo em estudo ? implementado de forma adaptativa, dada a forte rela??o n?o-linear entre o sinal de entrada e o erro de predi??o. Resultados de simula??o mostram a efici?ncia do controlador preditivo bilinear adaptativo em compara??o com o convencional.