Application Of Neural Networks To Adaptive Control Of Nonlinear Systems

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Application of Neural Networks to Adaptive Control of Nonlinear Systems

G. W. Ng
Application of Neural Networks to Adaptive Control of Nonlinear Systems Book PDF

Author : G. W. Ng
Publisher : Wiley
Page : 224 pages
File Size : 46,5 Mb
Release : 1997-04-30
Category : Science
ISBN : 0471972630

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Application of Neural Networks to Adaptive Control of Nonlinear Systems by G. W. Ng Pdf

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.

Neural Network-Based Adaptive Control of Uncertain Nonlinear Systems

Kasra Esfandiari,Farzaneh Abdollahi,Heidar A. Talebi
Neural Network Based Adaptive Control of Uncertain Nonlinear Systems Book PDF

Author : Kasra Esfandiari,Farzaneh Abdollahi,Heidar A. Talebi
Publisher : Springer Nature
Page : 181 pages
File Size : 49,7 Mb
Release : 2021-06-18
Category : Technology & Engineering
ISBN : 9783030731366

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Neural Network-Based Adaptive Control of Uncertain Nonlinear Systems by Kasra Esfandiari,Farzaneh Abdollahi,Heidar A. Talebi Pdf

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.

Adaptive Sliding Mode Neural Network Control for Nonlinear Systems

Yang Li,Jianhua Zhang,Wu Qiong
Adaptive Sliding Mode Neural Network Control for Nonlinear Systems Book PDF

Author : Yang Li,Jianhua Zhang,Wu Qiong
Publisher : Academic Press
Page : 186 pages
File Size : 52,7 Mb
Release : 2018-11-16
Category : Technology & Engineering
ISBN : 9780128154328

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Adaptive Sliding Mode Neural Network Control for Nonlinear Systems by Yang Li,Jianhua Zhang,Wu Qiong Pdf

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

Applications Of Neural Adaptive Control Technology

Andrzej Dzielinski,Jens Kalkkuhl,Rafal Zbikowski,Kenneth J Hunt
Applications Of Neural Adaptive Control Technology Book PDF

Author : Andrzej Dzielinski,Jens Kalkkuhl,Rafal Zbikowski,Kenneth J Hunt
Publisher : World Scientific
Page : 318 pages
File Size : 55,5 Mb
Release : 1997-09-02
Category : Computers
ISBN : 9789814497336

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Applications Of Neural Adaptive Control Technology by Andrzej Dzielinski,Jens Kalkkuhl,Rafal Zbikowski,Kenneth J Hunt Pdf

This book presents the results of the second workshop on Neural Adaptive Control Technology, NACT II, held on September 9-10, 1996, in Berlin. The workshop was organised in connection with a three-year European-Union-funded Basic Research Project in the ESPRIT framework, called NACT, a collaboration between Daimler-Benz (Germany) and the University of Glasgow (Scotland).The NACT project, which began on 1 April 1994, is a study of the fundamental properties of neural-network-based adaptive control systems. Where possible, links with traditional adaptive control systems are exploited. A major aim is to develop a systematic engineering procedure for designing neural controllers for nonlinear dynamic systems. The techniques developed are being evaluated on concrete industrial problems from within the Daimler-Benz group of companies.The aim of the workshop was to bring together selected invited specialists in the fields of adaptive control, nonlinear systems and neural networks. The first workshop (NACT I) took place in Glasgow in May 1995 and was mainly devoted to theoretical issues of neural adaptive control. Besides monitoring further development of theory, the NACT II workshop was focused on industrial applications and software tools. This context dictated the focus of the book and guided the editors in the choice of the papers and their subsequent reshaping into substantive book chapters. Thus, with the project having progressed into its applications stage, emphasis is put on the transfer of theory of neural adaptive engineering into industrial practice. The contributors are therefore both renowned academics and practitioners from major industrial users of neurocontrol.

Neural Network Control of Nonlinear Discrete-Time Systems

Jagannathan Sarangapani
Neural Network Control of Nonlinear Discrete Time Systems Book PDF

Author : Jagannathan Sarangapani
Publisher : CRC Press
Page : 624 pages
File Size : 47,7 Mb
Release : 2018-10-03
Category : Technology & Engineering
ISBN : 9781420015454

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Neural Network Control of Nonlinear Discrete-Time Systems by Jagannathan Sarangapani Pdf

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.

Stable Adaptive Neural Network Control

S.S. Ge,C.C. Hang,T.H. Lee,Tao Zhang
Stable Adaptive Neural Network Control Book PDF

Author : S.S. Ge,C.C. Hang,T.H. Lee,Tao Zhang
Publisher : Springer Science & Business Media
Page : 296 pages
File Size : 48,9 Mb
Release : 2013-03-09
Category : Science
ISBN : 9781475765779

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Stable Adaptive Neural Network Control by S.S. Ge,C.C. Hang,T.H. Lee,Tao Zhang Pdf

Recent years have seen a rapid development of neural network control tech niques and their successful applications. Numerous simulation studies and actual industrial implementations show that artificial neural network is a good candidate for function approximation and control system design in solving the control problems of complex nonlinear systems in the presence of different kinds of uncertainties. Many control approaches/methods, reporting inventions and control applications within the fields of adaptive control, neural control and fuzzy systems, have been published in various books, journals and conference proceedings. In spite of these remarkable advances in neural control field, due to the complexity of nonlinear systems, the present research on adaptive neural control is still focused on the development of fundamental methodologies. From a theoretical viewpoint, there is, in general, lack of a firmly mathematical basis in stability, robustness, and performance analysis of neural network adaptive control systems. This book is motivated by the need for systematic design approaches for stable adaptive control using approximation-based techniques. The main objec tives of the book are to develop stable adaptive neural control strategies, and to perform transient performance analysis of the resulted neural control systems analytically. Other linear-in-the-parameter function approximators can replace the linear-in-the-parameter neural networks in the controllers presented in the book without any difficulty, which include polynomials, splines, fuzzy systems, wavelet networks, among others. Stability is one of the most important issues being concerned if an adaptive neural network controller is to be used in practical applications.

Stable Adaptive Control and Estimation for Nonlinear Systems

Jeffrey T. Spooner,Manfredi Maggiore,Raúl Ordóñez,Kevin M. Passino
Stable Adaptive Control and Estimation for Nonlinear Systems Book PDF

Author : Jeffrey T. Spooner,Manfredi Maggiore,Raúl Ordóñez,Kevin M. Passino
Publisher : John Wiley & Sons
Page : 564 pages
File Size : 48,6 Mb
Release : 2004-04-07
Category : Science
ISBN : 9780471460978

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Stable Adaptive Control and Estimation for Nonlinear Systems by Jeffrey T. Spooner,Manfredi Maggiore,Raúl Ordóñez,Kevin M. Passino Pdf

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.

Adaptive Control with Recurrent High-order Neural Networks

George A. Rovithakis,Manolis A. Christodoulou
Adaptive Control with Recurrent High order Neural Networks Book PDF

Author : George A. Rovithakis,Manolis A. Christodoulou
Publisher : Springer Science & Business Media
Page : 203 pages
File Size : 51,6 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9781447107859

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Adaptive Control with Recurrent High-order Neural Networks by George A. Rovithakis,Manolis A. Christodoulou Pdf

The series Advances in Industrial Control aims to report and encourage technology transfer in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. New theory, new controllers, actuators, sensors, new industrial processes, computer methods, new applications, new philosophies ... , new challenges. Much of this development work resides in industrial reports, feasibility study papers and the reports of advanced collaborative projects. The series offers an opportunity for researchers to present an extended exposition of such new work in all aspects of industrial control for wider and rapid dissemination. Neural networks is one of those areas where an initial burst of enthusiasm and optimism leads to an explosion of papers in the journals and many presentations at conferences but it is only in the last decade that significant theoretical work on stability, convergence and robustness for the use of neural networks in control systems has been tackled. George Rovithakis and Manolis Christodoulou have been interested in these theoretical problems and in the practical aspects of neural network applications to industrial problems. This very welcome addition to the Advances in Industrial Control series provides a succinct report of their research. The neural network model at the core of their work is the Recurrent High Order Neural Network (RHONN) and a complete theoretical and simulation development is presented. Different readers will find different aspects of the development of interest. The last chapter of the monograph discusses the problem of manufacturing or production process scheduling.

Differential Neural Networks for Robust Nonlinear Control

Alexander S. Poznyak,Edgar N. Sanchez,Wen Yu (profesor titular.)
Differential Neural Networks for Robust Nonlinear Control Book PDF

Author : Alexander S. Poznyak,Edgar N. Sanchez,Wen Yu (profesor titular.)
Publisher : World Scientific
Page : 464 pages
File Size : 50,5 Mb
Release : 2001
Category : Science
ISBN : 981281129X

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Differential Neural Networks for Robust Nonlinear Control by Alexander S. Poznyak,Edgar N. Sanchez,Wen Yu (profesor titular.) Pdf

This book deals with continuous time dynamic neural networks theory applied to the solution of basic problems in robust control theory, including identification, state space estimation (based on neuro-observers) and trajectory tracking. The plants to be identified and controlled are assumed to be a priori unknown but belonging to a given class containing internal unmodelled dynamics and external perturbations as well. The error stability analysis and the corresponding error bounds for different problems are presented. The effectiveness of the suggested approach is illustrated by its application to various controlled physical systems (robotic, chaotic, chemical, etc.). Contents: Theoretical Study: Neural Networks Structures; Nonlinear System Identification: Differential Learning; Sliding Mode Identification: Algebraic Learning; Neural State Estimation; Passivation via Neuro Control; Neuro Trajectory Tracking; Neurocontrol Applications: Neural Control for Chaos; Neuro Control for Robot Manipulators; Identification of Chemical Processes; Neuro Control for Distillation Column; General Conclusions and Future Work; Appendices: Some Useful Mathematical Facts; Elements of Qualitative Theory of ODE; Locally Optimal Control and Optimization. Readership: Graduate students, researchers, academics/lecturers and industrialists in neural networks.

Fully Tuned Radial Basis Function Neural Networks for Flight Control

N. Sundararajan,P. Saratchandran,Yan Li
Fully Tuned Radial Basis Function Neural Networks for Flight Control Book PDF

Author : N. Sundararajan,P. Saratchandran,Yan Li
Publisher : Springer Science & Business Media
Page : 167 pages
File Size : 51,9 Mb
Release : 2013-03-09
Category : Science
ISBN : 9781475752861

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Fully Tuned Radial Basis Function Neural Networks for Flight Control by N. Sundararajan,P. Saratchandran,Yan Li Pdf

Fully Tuned Radial Basis Function Neural Networks for Flight Control presents the use of the Radial Basis Function (RBF) neural networks for adaptive control of nonlinear systems with emphasis on flight control applications. A Lyapunov synthesis approach is used to derive the tuning rules for the RBF controller parameters in order to guarantee the stability of the closed loop system. Unlike previous methods that tune only the weights of the RBF network, this book presents the derivation of the tuning law for tuning the centers, widths, and weights of the RBF network, and compares the results with existing algorithms. It also includes a detailed review of system identification, including indirect and direct adaptive control of nonlinear systems using neural networks. Fully Tuned Radial Basis Function Neural Networks for Flight Control is an excellent resource for professionals using neural adaptive controllers for flight control applications.

Identification and Adaptive Control for Nonlinear Systems and Applications

Jianhua Zhang,Yang Li,Qiang Chen
Identification and Adaptive Control for Nonlinear Systems and Applications Book PDF

Author : Jianhua Zhang,Yang Li,Qiang Chen
Publisher : Academic Press
Page : 320 pages
File Size : 45,8 Mb
Release : 2022-03-15
Category : Mathematics
ISBN : 0128234415

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Identification and Adaptive Control for Nonlinear Systems and Applications by Jianhua Zhang,Yang Li,Qiang Chen Pdf

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

Evolutionary Learning Algorithms for Neural Adaptive Control

Dimitris C. Dracopoulos
Evolutionary Learning Algorithms for Neural Adaptive Control Book PDF

Author : Dimitris C. Dracopoulos
Publisher : Springer
Page : 214 pages
File Size : 48,7 Mb
Release : 2013-12-21
Category : Computers
ISBN : 9781447109037

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Evolutionary Learning Algorithms for Neural Adaptive Control by Dimitris C. Dracopoulos Pdf

Evolutionary Learning Algorithms for Neural Adaptive Control is an advanced textbook, which investigates how neural networks and genetic algorithms can be applied to difficult adaptive control problems which conventional results are either unable to solve , or for which they can not provide satisfactory results. It focuses on the principles involved, rather than on the modelling of the applications themselves, and therefore provides the reader with a good introduction to the fundamental issues involved.

Intelligent Adaptive Control

Lakhmi C. Jain,Clarence W. de Silva
Intelligent Adaptive Control Book PDF

Author : Lakhmi C. Jain,Clarence W. de Silva
Publisher : CRC Press
Page : 440 pages
File Size : 54,7 Mb
Release : 1998-12-29
Category : Computers
ISBN : 0849398053

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Intelligent Adaptive Control by Lakhmi C. Jain,Clarence W. de Silva Pdf

This book describes important techniques, developments, and applications of computational intelligence in system control. Chapters present: an introduction to the fundamentals of neural networks, fuzzy logic, and evolutionary computing a rigorous treatment of intelligent control industrial applications of intelligent control and soft computing, including transportation, petroleum, motor drive, industrial automation, and fish processing other knowledge-based techniques, including vehicle driving aid and air traffic management Intelligent Adaptive Control provides a state-of-the-art treatment of practical applications of computational intelligence in system control. The book cohesively covers introductory and advanced theory, design, implementation, and industrial use - serving as a singular resource for the theory and application of intelligent control, particularly employing fuzzy logic, neural networks, and evolutionary computing.

Neural Network Control

Sunan Huang,Kok Kiong Tan,Kok Zuea Tang
Neural Network Control Book PDF

Author : Sunan Huang,Kok Kiong Tan,Kok Zuea Tang
Publisher : Research Studies Press Limited
Page : 424 pages
File Size : 52,7 Mb
Release : 2004
Category : Computers
ISBN : UOM:39015059151913

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Neural Network Control by Sunan Huang,Kok Kiong Tan,Kok Zuea Tang Pdf

"While the book is written to serve as an advanced control reference on NN control for researchers, postgraduates and senior undergraduates, it should be equally useful to those industrial practitioners who are keen to explore the use of advanced neural network control in real problems. The prerequisite for gaining maximum benefit from this book is a basic knowledge of control systems, such as that imparted by a first undergraduate course on control systems engineering."--Jacket.

Nonlinear Identification and Control

G.P. Liu
Nonlinear Identification and Control Book PDF

Author : G.P. Liu
Publisher : Springer Science & Business Media
Page : 224 pages
File Size : 44,6 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9781447103455

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Nonlinear Identification and Control by G.P. Liu Pdf

The purpose of this monograph is to give the broad aspects of nonlinear identification and control using neural networks. It uses a number of simulated and industrial examples throughout, to demonstrate the operation of nonlinear identification and control techniques using neural networks.