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Applications of Neural Adaptive Control Technology

1997 Technology & Engineering
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Release : 1997
Genre : Technology & Engineering
Kind : eBook
Book Rating : 514/5 ( reviews)

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Book Synopsis Applications of Neural Adaptive Control Technology by : Jens Kalkkuhl

Download or read book Applications of Neural Adaptive Control Technology written by Jens Kalkkuhl. This book was released on 1997. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Application of Neural Networks to Adaptive Control of Nonlinear Systems

1997 Adaptive control systems
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Release : 1997
Genre : Adaptive control systems
Kind : eBook
Book Rating : 140/5 ( reviews)

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Book Synopsis Application of Neural Networks to Adaptive Control of Nonlinear Systems by : Gee Wah Ng

Download or read book Application of Neural Networks to Adaptive Control of Nonlinear Systems written by Gee Wah Ng. This book was released on 1997. 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 to train 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 are presented.

Neural Network-Based Adaptive Control of Uncertain Nonlinear Systems

2021-06-18 Technology & Engineering
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Release : 2021-06-18
Genre : Technology & Engineering
Kind : eBook
Book Rating : 367/5 ( reviews)

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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. This book was released on 2021-06-18. 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.

Adaptive Sliding Mode Neural Network Control for Nonlinear Systems

2018-11-16 Technology & Engineering
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Release : 2018-11-16
Genre : Technology & Engineering
Kind : eBook
Book Rating : 322/5 ( reviews)

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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. This book was released on 2018-11-16. 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

Neural Network Control of Nonlinear Discrete-Time Systems

2018-10-03 Technology & Engineering
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Release : 2018-10-03
Genre : Technology & Engineering
Kind : eBook
Book Rating : 451/5 ( reviews)

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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. This book was released on 2018-10-03. 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.

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