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Author: Rafa? ?bikowski
Publisher: World Scientific
ISBN: 9789810225575
Category : Technology & Engineering
Languages : en
Pages : 368
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Book Description
This book is an outgrowth of the workshop on Neural Adaptive Control Technology, NACT I, held in 1995 in Glasgow. Selected workshop participants were asked to substantially expand and revise their contributions to make them into full papers.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). A major aim of the NACT project 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 Daimler-Benz.In the book emphasis is put on development of sound theory of neural adaptive control for nonlinear control systems, but firmly anchored in the engineering context of industrial practice. Therefore the contributors are both renowned academics and practitioners from major industrial users of neurocontrol.
Author: Rafa? ?bikowski
Publisher: World Scientific
ISBN: 9789810225575
Category : Technology & Engineering
Languages : en
Pages : 368
Get Book Here
Book Description
This book is an outgrowth of the workshop on Neural Adaptive Control Technology, NACT I, held in 1995 in Glasgow. Selected workshop participants were asked to substantially expand and revise their contributions to make them into full papers.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). A major aim of the NACT project 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 Daimler-Benz.In the book emphasis is put on development of sound theory of neural adaptive control for nonlinear control systems, but firmly anchored in the engineering context of industrial practice. Therefore the contributors are both renowned academics and practitioners from major industrial users of neurocontrol.
Author: Alessandro Astolfi
Publisher: Springer Science & Business Media
ISBN: 1848000669
Category : Technology & Engineering
Languages : en
Pages : 302
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Book Description
The authors here provide a detailed treatment of the design of robust adaptive controllers for nonlinear systems with uncertainties. They employ a new tool based on the ideas of system immersion and manifold invariance. New algorithms are delivered for the construction of robust asymptotically-stabilizing and adaptive control laws for nonlinear systems. The methods proposed lead to modular schemes that are easier to tune than their counterparts obtained from Lyapunov redesign.
Author: Kasra Esfandiari
Publisher: Springer Nature
ISBN: 3030731367
Category : Technology & Engineering
Languages : en
Pages : 181
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Book Description
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.
Author: Jens Kalkkuhl
Publisher: World Scientific
ISBN: 9789810231514
Category : Technology & Engineering
Languages : en
Pages : 328
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Book Description
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.
Author: A.E. Ruano
Publisher: IET
ISBN: 0863414893
Category : Computers
Languages : en
Pages : 478
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Book Description
Intelligent Control techniques are becoming important tools in both academia and industry. Methodologies developed in the field of soft-computing, such as neural networks, fuzzy systems and evolutionary computation, can lead to accommodation of more complex processes, improved performance and considerable time savings and cost reductions. Intelligent Control Systems using Computational Intellingence Techniques details the application of these tools to the field of control systems. Each chapter gives and overview of current approaches in the topic covered, with a set of the most important references in the field, and then details the author's approach, examining both the theory and practical applications.
Author: Sung-Bae Cho
Publisher: World Scientific
ISBN: 9812810285
Category : Computers
Languages : en
Pages : 439
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Book Description
Ch. 1. Automatic detection of microcalcifications in mammograms using a fuzzy classifier / A. P. Drijarkara, G. Naghdy, F. Naghdy -- ch. 2. Software deployability control system: application of Choquet integral and rough sets / James F. Peters III, Sheela Ramanna -- ch. 3. Predictive fuzzy model for control of an artificial muscle / Petar B. Petrovic -- ch. 4. Fuzzy supervisory control with fuzzy-PID controller and its application to petroleum plants / Tetsuji Tani, Hiroaki Kobayashi, Takeshi Furuhashi -- ch. 5. Genetic algorithm-based predictive control for nonlinear processes / Seung C. Shin, Zeungnam Bien -- ch. 6. Indirect neuro-control for multivariable nonlinear systems with application to 2-bar load systems / Jun Oh Jang, Hee Tae Chung -- ch. 7. Evolutionary computation for information retrieval based on user preference / Hak-Gyoon Kim, Sung-Bae Cho -- ch. 8. On-line tool condition monitoring based on a neurofuzzy intelligent signal feature classification procedure / Pan Fu, A. D. Hope, G. A. King -- ch. 9. Feature extraction by self-organized fuzzy templates with applications / Eiji Uchino, Shigeru Nakashima, Takeshi Yamakawa -- ch. 10. Inference of self-excited vibration in high-speed end-milling based on fuzzy neural networks / Chuanxin Su, Junichi Hino, Toshio Yoshimura -- ch. 11. Fuzzy logic and neural networks approach -- a way to improve overall performance of integrated heating systems / Evgueniy Entchev -- ch. 12. Application of fuzzy pattern matching and genetic algorithms to rotating machinery diagnosis / Jesus M. Fernandez Salido, Shuta Murakami -- ch. 13. Design and tuning a neurofuzzy power system stabilizer using genetic algorithms / Ali Afzalian, Derek A. Linkens -- ch. 14. Techniques of soft computing for emergency management in a mineral oils deposit / Alessandro De Carli, Sonia Pisani -- ch. 15. An application of logic programs with soft computing aspects to fault diagnosis in digital circuits / Hiroshi Sakai, Atsushi Imamoto, Akimichi Okuma -- ch. 16. Determination of the motion parameters from the perspective projection of a triangle / Myint Myint Sein, Hiromitsu Hama.
Author: S.S. Ge
Publisher: Springer Science & Business Media
ISBN: 1475765770
Category : Science
Languages : en
Pages : 296
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Book Description
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.
Author: Jeffrey T. Spooner
Publisher: John Wiley & Sons
ISBN: 0471460974
Category : Science
Languages : en
Pages : 564
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Book Description
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.
Author: Gang Tao
Publisher: Wiley-Interscience
ISBN:
Category : Mathematics
Languages : en
Pages : 320
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Book Description
The authors present an effective approach to handle some of the most common types of component imperfections encountered in industrial automation, consumer electroncis, and defence and transportation systems.
Author: Jay A. Farrell
Publisher: John Wiley & Sons
ISBN: 0471781800
Category : Science
Languages : en
Pages : 440
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Book Description
A highly accessible and unified approach to the design and analysis of intelligent control systems Adaptive Approximation Based Control is a tool every control designer should have in his or her control toolbox. Mixing approximation theory, parameter estimation, and feedback control, this book presents a unified approach designed to enable readers to apply adaptive approximation based control to existing systems, and, more importantly, to gain enough intuition and understanding to manipulate and combine it with other control tools for applications that have not been encountered before. The authors provide readers with a thought-provoking framework for rigorously considering such questions as: * What properties should the function approximator have? * Are certain families of approximators superior to others? * Can the stability and the convergence of the approximator parameters be guaranteed? * Can control systems be designed to be robust in the face of noise, disturbances, and unmodeled effects? * Can this approach handle significant changes in the dynamics due to such disruptions as system failure? * What types of nonlinear dynamic systems are amenable to this approach? * What are the limitations of adaptive approximation based control? Combining theoretical formulation and design techniques with extensive use of simulation examples, this book is a stimulating text for researchers and graduate students and a valuable resource for practicing engineers.
