Adaptive Sliding Mode Neural Network Control for Nonlinear Systems

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Publisher : Academic Press
ISBN 13 : 0128154322
Total Pages : 186 pages
Book Rating : 4.28/5 ( download)

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Book Synopsis Adaptive Sliding Mode Neural Network Control for Nonlinear Systems by : Yang Li

Download or read book Adaptive Sliding Mode Neural Network Control for Nonlinear Systems written by Yang Li and published by Academic Press. This book was released on 2018-11-16 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

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Publisher : Academic Press
ISBN 13 : 9780128234419
Total Pages : 320 pages
Book Rating : 4.15/5 ( download)

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Book Synopsis Identification and Adaptive Control for Nonlinear Systems and Applications by : Jianhua Zhang

Download or read book Identification and Adaptive Control for Nonlinear Systems and Applications written by Jianhua Zhang and published by Academic Press. This book was released on 2022-03-15 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

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Publisher : Springer
ISBN 13 : 3319111736
Total Pages : 592 pages
Book Rating : 4.35/5 ( download)

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Book Synopsis Advances and Applications in Sliding Mode Control systems by : Ahmad Taher Azar

Download or read book Advances and Applications in Sliding Mode Control systems written by Ahmad Taher Azar and published by Springer. This book was released on 2014-11-01 with total page 592 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Stable Adaptive Control and Estimation for Nonlinear Systems

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Publisher : John Wiley & Sons
ISBN 13 : 0471460974
Total Pages : 564 pages
Book Rating : 4.78/5 ( download)

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Book Synopsis Stable Adaptive Control and Estimation for Nonlinear Systems by : Jeffrey T. Spooner

Download or read book Stable Adaptive Control and Estimation for Nonlinear Systems written by Jeffrey T. Spooner and published by John Wiley & Sons. This book was released on 2004-04-07 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Neural Network Control of Nonlinear Discrete-Time Systems

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Publisher : CRC Press
ISBN 13 : 1420015451
Total Pages : 624 pages
Book Rating : 4.54/5 ( download)

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Book Synopsis Neural Network Control of Nonlinear Discrete-Time Systems by : Jagannathan Sarangapani

Download or read book Neural Network Control of Nonlinear Discrete-Time Systems written by Jagannathan Sarangapani and published by CRC Press. This book was released on 2018-10-03 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Advances in Sliding Mode Control

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Publisher : Springer
ISBN 13 : 3642369863
Total Pages : 388 pages
Book Rating : 4.65/5 ( download)

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Book Synopsis Advances in Sliding Mode Control by : B Bandyopadhyay

Download or read book Advances in Sliding Mode Control written by B Bandyopadhyay and published by Springer. This book was released on 2013-03-15 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: The sliding mode control paradigm has become a mature technique for the design of robust controllers for a wide class of systems including nonlinear, uncertain and time-delayed systems. This book is a collection of plenary and invited talks delivered at the 12th IEEE International Workshop on Variable Structure System held at the Indian Institute of Technology, Mumbai, India in January 2012. After the workshop, these researchers were invited to develop book chapters for this edited collection in order to reflect the latest results and open research questions in the area. The contributed chapters have been organized by the editors to reflect the various themes of sliding mode control which are the current areas of theoretical research and applications focus; namely articulation of the fundamental underpinning theory of the sliding mode design paradigm, sliding modes for decentralized system representations, control of time-delay systems, the higher order sliding mode concept, results applicable to nonlinear and underactuated systems, sliding mode observers, discrete sliding mode control together with cutting edge research contributions in the application of the sliding mode concept to real world problems. This book provides the reader with a clear and complete picture of the current trends in Variable Structure Systems and Sliding Mode Control Theory.

Neural Network-Based Adaptive Control of Uncertain Nonlinear Systems

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Publisher : Springer Nature
ISBN 13 : 3030731367
Total Pages : 181 pages
Book Rating : 4.66/5 ( download)

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Book Synopsis Neural Network-Based Adaptive Control of Uncertain Nonlinear Systems by : Kasra Esfandiari

Download or read book Neural Network-Based Adaptive Control of Uncertain Nonlinear Systems written by Kasra Esfandiari and published by Springer Nature. This book was released on 2021-06-18 with total page 181 pages. Available in PDF, EPUB and Kindle. Book excerpt: The focus of this book is the application of artificial neural networks in uncertain dynamical systems. It explains how to use neural networks in concert with adaptive techniques for system identification, state estimation, and control problems. The authors begin with a brief historical overview of adaptive control, followed by a review of mathematical preliminaries. In the subsequent chapters, they present several neural network-based control schemes. Each chapter starts with a concise introduction to the problem under study, and a neural network-based control strategy is designed for the simplest case scenario. After these designs are discussed, different practical limitations (i.e., saturation constraints and unavailability of all system states) are gradually added, and other control schemes are developed based on the primary scenario. Through these exercises, the authors present structures that not only provide mathematical tools for navigating control problems, but also supply solutions that are pertinent to real-life systems.

Parameter Estimation and Adaptive Control for Nonlinear Servo Systems

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Publisher : Elsevier
ISBN 13 : 0443155755
Total Pages : 304 pages
Book Rating : 4.58/5 ( download)

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Book Synopsis Parameter Estimation and Adaptive Control for Nonlinear Servo Systems by : Shubo Wang

Download or read book Parameter Estimation and Adaptive Control for Nonlinear Servo Systems written by Shubo Wang and published by Elsevier. This book was released on 2024-02-01 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Sliding Mode Control and Observation

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Publisher : Springer Science & Business Media
ISBN 13 : 0817648933
Total Pages : 356 pages
Book Rating : 4.30/5 ( download)

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Book Synopsis Sliding Mode Control and Observation by : Yuri Shtessel

Download or read book Sliding Mode Control and Observation written by Yuri Shtessel and published by Springer Science & Business Media. This book was released on 2013-06-01 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: The sliding mode control methodology has proven effective in dealing with complex dynamical systems affected by disturbances, uncertainties and unmodeled dynamics. Robust control technology based on this methodology has been applied to many real-world problems, especially in the areas of aerospace control, electric power systems, electromechanical systems, and robotics. Sliding Mode Control and Observation represents the first textbook that starts with classical sliding mode control techniques and progresses toward newly developed higher-order sliding mode control and observation algorithms and their applications. The present volume addresses a range of sliding mode control issues, including: *Conventional sliding mode controller and observer design *Second-order sliding mode controllers and differentiators *Frequency domain analysis of conventional and second-order sliding mode controllers *Higher-order sliding mode controllers and differentiators *Higher-order sliding mode observers *Sliding mode disturbance observer based control *Numerous applications, including reusable launch vehicle and satellite formation control, blood glucose regulation, and car steering control are used as case studies Sliding Mode Control and Observation is aimed at graduate students with a basic knowledge of classical control theory and some knowledge of state-space methods and nonlinear systems, while being of interest to a wider audience of graduate students in electrical/mechanical/aerospace engineering and applied mathematics, as well as researchers in electrical, computer, chemical, civil, mechanical, aeronautical, and industrial engineering, applied mathematicians, control engineers, and physicists. Sliding Mode Control and Observation provides the necessary tools for graduate students, researchers and engineers to robustly control complex and uncertain nonlinear dynamical systems. Exercises provided at the end of each chapter make this an ideal text for an advanced course taught in control theory.

Application of Neural Networks to Adaptive Control of Nonlinear Systems

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Author :
Publisher : Wiley
ISBN 13 : 9780471972631
Total Pages : 224 pages
Book Rating : 4.30/5 ( download)

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Book Synopsis Application of Neural Networks to Adaptive Control of Nonlinear Systems by : G. W. Ng

Download or read book Application of Neural Networks to Adaptive Control of Nonlinear Systems written by G. W. Ng and published by Wiley. This book was released on 1997-04-30 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.