Adaptive Sliding Mode Neural Network Control For Nonlinear Systems


Adaptive Sliding Mode Neural Network Control For Nonlinear Systems
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Adaptive Sliding Mode Neural Network Control For Nonlinear Systems


Adaptive Sliding Mode Neural Network Control For Nonlinear Systems
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Author : Yang Li
language : en
Publisher: Academic Press
Release Date : 2018-11-16

Adaptive Sliding Mode Neural Network Control For Nonlinear Systems written by Yang Li and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-16 with Technology & Engineering categories.


Adaptive Sliding Mode Neural Network Control for Nonlinear Systems introduces nonlinear systems basic knowledge, analysis and control methods, and applications in various fields. It offers instructive examples and simulations, along with the source codes, and provides the basic architecture of control science and engineering. Introduces nonlinear systems' basic knowledge, analysis and control methods, along with applications in various fields Offers instructive examples and simulations, including source codes Provides the basic architecture of control science and engineering



Identification And Adaptive Control For Nonlinear Systems And Applications


Identification And Adaptive Control For Nonlinear Systems And Applications
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Author : Jianhua Zhang
language : en
Publisher: Academic Press
Release Date : 2022-03-15

Identification And Adaptive Control For Nonlinear Systems And Applications written by Jianhua Zhang and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-15 with Mathematics categories.


Identification and Adaptive Control for Nonlinear Systems and Applications: Applied Mathematics in Control Engineering introduces nonlinear systems concepts, system analysis, system control methods and applications in various fields. The major contribution of the book includes: (1) The basic concepts of nonlinear systems stability analysis and nonlinear systems control method. (2) The stability analysis of complex nonlinear system with adaptive neural networks control. (3) The nonlinear systems adaptive sliding mode controller design of complex nonlinear systems. (4) Some industrial application. The book gives an introduction to basic nonlinear systems architectures for adaptive control methods. Emphasis is placed on the mathematical analysis of these systems, on methods of controlling them for adaptive control and on their application to practical engineering problems in such areas as aircraft path planning. This book enables audience to understand the basic architectures of control science and engineering, and to master classical and advanced design method for nonlinear system. Introduces nonlinear systems concepts, system analysis, system control methods and applications in various fields Presents basic concepts of nonlinear systems stability analysis and nonlinear systems control method Offers practical examples



Advances And Applications In Sliding Mode Control Systems


Advances And Applications In Sliding Mode Control Systems
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Author : Ahmad Taher Azar
language : en
Publisher: Springer
Release Date : 2014-11-01

Advances And Applications In Sliding Mode Control Systems written by Ahmad Taher Azar and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-01 with Technology & Engineering categories.


This book describes the advances and applications in Sliding mode control (SMC) which is widely used as a powerful method to tackle uncertain nonlinear systems. The book is organized into 21 chapters which have been organised by the editors to reflect the various themes of sliding mode control. The book provides the reader with a broad range of material from first principles up to the current state of the art in the area of SMC and observation presented in a clear, matter-of-fact style. As such it is appropriate for graduate students with a basic knowledge of classical control theory and some knowledge of state-space methods and nonlinear systems. The resulting design procedures are emphasized using Matlab/Simulink software.



Sliding Mode Control Using Matlab


Sliding Mode Control Using Matlab
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Author : Jinkun Liu
language : en
Publisher: Academic Press
Release Date : 2017-05-25

Sliding Mode Control Using Matlab written by Jinkun Liu and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-25 with Technology & Engineering categories.


Sliding Mode Control Using MATLAB provides many sliding mode controller design examples, along with simulation examples and MATLAB® programs. Following the review of sliding mode control, the book includes sliding mode control for continuous systems, robust adaptive sliding mode control, sliding mode control for underactuated systems, backstepping, and dynamic surface sliding mode control, sliding mode control based on filter and observer, sliding mode control for discrete systems, fuzzy sliding mode control, neural network sliding mode control, and sliding mode control for robot manipulators. The contents of each chapter are independent, providing readers with information they can use for their own needs. It is suitable for the readers who work on mechanical and electronic engineering, electrical automation engineering, etc., and can also be used as a teaching reference for universities. Provides many sliding mode controller design examples to help readers solve their research and design problems Includes various, implementable, robust sliding mode control design solutions from engineering applications Provides the simulation examples and MATLAB programs for each sliding mode control algorithm



Robust Adaptive Control For Fractional Order Systems With Disturbance And Saturation


Robust Adaptive Control For Fractional Order Systems With Disturbance And Saturation
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Author : Mou Chen
language : en
Publisher: John Wiley & Sons
Release Date : 2017-10-20

Robust Adaptive Control For Fractional Order Systems With Disturbance And Saturation written by Mou Chen and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-20 with Technology & Engineering categories.


A treatise on investigating tracking control and synchronization control of fractional-order nonlinear systems with system uncertainties, external disturbance, and input saturation Robust Adaptive Control for Fractional-Order Systems, with Disturbance and Saturation provides the reader with a good understanding on how to achieve tracking control and synchronization control of fractional-order nonlinear systems with system uncertainties, external disturbance, and input saturation. Although some texts have touched upon control of fractional-order systems, the issues of input saturation and disturbances have rarely been considered together. This book offers chapter coverage of fractional calculus and fractional-order systems; fractional-order PID controller and fractional-order disturbance observer; design of fractional-order controllers for nonlinear chaotic systems and some applications; sliding mode control for fractional-order nonlinear systems based on disturbance observer; disturbance observer based neural control for an uncertain fractional-order rotational mechanical system; adaptive neural tracking control for uncertain fractional-order chaotic systems subject to input saturation and disturbance; stabilization control of continuous-time fractional positive systems based on disturbance observer; sliding mode synchronization control for fractional-order chaotic systems with disturbance; and more. Based on the approximation ability of the neural network (NN), the adaptive neural control schemes are reported for uncertain fractional-order nonlinear systems Covers the disturbance estimation techniques that have been developed to alleviate the restriction faced by traditional feedforward control and reject the effect of external disturbances for uncertain fractional-order nonlinear systems By combining the NN with the disturbance observer, the disturbance observer based adaptive neural control schemes have been studied for uncertain fractional-order nonlinear systems with unknown disturbances Considers, together, the issue of input saturation and the disturbance for the control of fractional-order nonlinear systems in the present of system uncertainty, external disturbance, and input saturation Robust Adaptive Control for Fractional-Order Systems, with Disturbance and Saturation can be used as a reference for the academic research on fractional-order nonlinear systems or used in Ph.D. study of control theory and engineering.



Stable Adaptive Control And Estimation For Nonlinear Systems


Stable Adaptive Control And Estimation For Nonlinear Systems
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Author : Jeffrey T. Spooner
language : en
Publisher: John Wiley & Sons
Release Date : 2004-04-07

Stable Adaptive Control And Estimation For Nonlinear Systems written by Jeffrey T. Spooner and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-04-07 with Science categories.


Thema dieses Buches ist die Anwendung neuronaler Netze und Fuzzy-Logic-Methoden zur Identifikation und Steuerung nichtlinear-dynamischer Systeme. Dabei werden fortgeschrittene Konzepte der herkömmlichen Steuerungstheorie mit den intuitiven Eigenschaften intelligenter Systeme kombiniert, um praxisrelevante Steuerungsaufgaben zu lösen. Die Autoren bieten viel Hintergrundmaterial; ausgearbeitete Beispiele und Übungsaufgaben helfen Studenten und Praktikern beim Vertiefen des Stoffes. Lösungen zu den Aufgaben sowie MATLAB-Codebeispiele sind ebenfalls enthalten.



Deep Reinforcement Learning With Guaranteed Performance


Deep Reinforcement Learning With Guaranteed Performance
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Author : Yinyan Zhang
language : en
Publisher: Springer Nature
Release Date : 2019-11-09

Deep Reinforcement Learning With Guaranteed Performance written by Yinyan Zhang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-09 with Technology & Engineering categories.


This book discusses methods and algorithms for the near-optimal adaptive control of nonlinear systems, including the corresponding theoretical analysis and simulative examples, and presents two innovative methods for the redundancy resolution of redundant manipulators with consideration of parameter uncertainty and periodic disturbances. It also reports on a series of systematic investigations on a near-optimal adaptive control method based on the Taylor expansion, neural networks, estimator design approaches, and the idea of sliding mode control, focusing on the tracking control problem of nonlinear systems under different scenarios. The book culminates with a presentation of two new redundancy resolution methods; one addresses adaptive kinematic control of redundant manipulators, and the other centers on the effect of periodic input disturbance on redundancy resolution. Each self-contained chapter is clearly written, making the book accessible to graduate students as well as academic and industrial researchers in the fields of adaptive and optimal control, robotics, and dynamic neural networks.



Neural Network Control Of Nonlinear Discrete Time Systems


Neural Network Control Of Nonlinear Discrete Time Systems
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Author : Jagannathan Sarangapani
language : en
Publisher: CRC Press
Release Date : 2018-10-03

Neural Network Control Of Nonlinear Discrete Time Systems written by Jagannathan Sarangapani and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-03 with Technology & Engineering categories.


Intelligent systems are a hallmark of modern feedback control systems. But as these systems mature, we have come to expect higher levels of performance in speed and accuracy in the face of severe nonlinearities, disturbances, unforeseen dynamics, and unstructured uncertainties. Artificial neural networks offer a combination of adaptability, parallel processing, and learning capabilities that outperform other intelligent control methods in more complex systems. Borrowing from Biology Examining neurocontroller design in discrete-time for the first time, Neural Network Control of Nonlinear Discrete-Time Systems presents powerful modern control techniques based on the parallelism and adaptive capabilities of biological nervous systems. At every step, the author derives rigorous stability proofs and presents simulation examples to demonstrate the concepts. Progressive Development After an introduction to neural networks, dynamical systems, control of nonlinear systems, and feedback linearization, the book builds systematically from actuator nonlinearities and strict feedback in nonlinear systems to nonstrict feedback, system identification, model reference adaptive control, and novel optimal control using the Hamilton-Jacobi-Bellman formulation. The author concludes by developing a framework for implementing intelligent control in actual industrial systems using embedded hardware. Neural Network Control of Nonlinear Discrete-Time Systems fosters an understanding of neural network controllers and explains how to build them using detailed derivations, stability analysis, and computer simulations.



Parameter Estimation And Adaptive Control For Nonlinear Servo Systems


Parameter Estimation And Adaptive Control For Nonlinear Servo Systems
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Author : Shubo Wang
language : en
Publisher: Elsevier
Release Date : 2024-02-01

Parameter Estimation And Adaptive Control For Nonlinear Servo Systems written by Shubo Wang and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-01 with Technology & Engineering categories.


Parameter Estimation and Adaptive Control for Nonlinear Servo Systems presents the latest advances in observer-based control design, focusing on adaptive control for nonlinear systems such as adaptive neural network control, adaptive parameter estimation, and system identification. This book offers an array of new real-world applications in the field. Written by eminent scientists in the field of control theory, this book covers the latest advances in observer-based control design. It provides fundamentals, algorithms, and it discusses key applications in the fields of power systems, robotics and mechatronics, flight and automotive systems. Presents a clear and concise introduction to the latest advances in parameter estimation and adaptive control with several concise applications for servo systems Covers a wide range of applications usually not found in similar books, such as power systems, robotics, mechatronics, aeronautics, and industrial systems Contains worked examples which make it ideal for advanced courses as well as for researchers starting to work in the field, particularly suitable for engineers wishing to enter the field quickly and efficiently



Application Of Neural Networks To Adaptive Control Of Nonlinear Systems


Application Of Neural Networks To Adaptive Control Of Nonlinear Systems
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Author : G. W. Ng
language : en
Publisher: Wiley
Release Date : 1997-04-30

Application Of Neural Networks To Adaptive Control Of Nonlinear Systems written by G. W. Ng and has been published by Wiley this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997-04-30 with Science categories.


This book investigates the ability of a neural network (NN) to learn how to control an unknown (nonlinear, in general) system, using data acquired on-line, that is during the process of attempting to exert control. Two algorithms are developed to train the neural network for real-time control applications. The first algorithm is known as Learning by Recursive Least Squares (LRLS) algorithm and the second algorithm is known as Integrated Gradient and Least Squares (IGLS) algorithm. The ability of these algorithms for training the NN controller for real-time control is demonstrated on practical applications and the local convergence and stability requirements of these algorithms are analysed. In addition, network topology, learning algorithms (particularly supervised learning) and neural network control strategies including a new classification system for them, are presented.