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Author : E. Colina Morles
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (6 download)
Download or read book Identification and Control of Dynamic Systems Via Adaptive Neural Networks written by E. Colina Morles and published by . This book was released on 1991 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Shahar Dror
Publisher :
ISBN 13 :
Total Pages : 258 pages
Book Rating : 4.:/5 (342 download)
Download or read book Identification and Control of Non-linear Time-varying Dynamical Systems Using Artificial Neural Networks written by Shahar Dror and published by . This book was released on 1992 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Alexander S. Poznyak
Publisher : World Scientific
ISBN 13 : 9789812811295
Total Pages : 464 pages
Book Rating : 4.8/5 (112 download)
Download or read book Differential Neural Networks for Robust Nonlinear Control written by Alexander S. Poznyak and published by World Scientific. This book was released on 2001 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : S. J. Oh
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (258 download)
Download or read book Identification and Control of Dynamic Systems Using Neural Networks written by S. J. Oh and published by . This book was released on 1993 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Gang Tao
Publisher : Springer Science & Business Media
ISBN 13 : 9781852333843
Total Pages : 430 pages
Book Rating : 4.3/5 (338 download)
Download or read book Adaptive Control of Nonsmooth Dynamic Systems written by Gang Tao and published by Springer Science & Business Media. This book was released on 2001-09-26 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many of the non-smooth, non-linear phenomena covered in this well-balanced book are of vital importance in almost any field of engineering. Contributors from all over the world ensure that no one area’s slant on the subjects predominates.
Author : Jens Kalkkuhl
Publisher : World Scientific
ISBN 13 : 9789810231514
Total Pages : 328 pages
Book Rating : 4.2/5 (315 download)
Download or read book Applications of Neural Adaptive Control Technology written by Jens Kalkkuhl and published by World Scientific. This book was released on 1997 with total page 328 pages. 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.
Author : Omid Omidvar
Publisher : Elsevier
ISBN 13 : 0080537391
Total Pages : 375 pages
Book Rating : 4.0/5 (85 download)
Download or read book Neural Systems for Control written by Omid Omidvar and published by Elsevier. This book was released on 1997-02-24 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: Control problems offer an industrially important application and a guide to understanding control systems for those working in Neural Networks. Neural Systems for Control represents the most up-to-date developments in the rapidly growing aplication area of neural networks and focuses on research in natural and artifical neural systems directly applicable to control or making use of modern control theory. The book covers such important new developments in control systems such as intelligent sensors in semiconductor wafer manufacturing; the relation between muscles and cerebral neurons in speech recognition; online compensation of reconfigurable control for spacecraft aircraft and other systems; applications to rolling mills, robotics and process control; the usage of past output data to identify nonlinear systems by neural networks; neural approximate optimal control; model-free nonlinear control; and neural control based on a regulation of physiological investigation/blood pressure control. All researchers and students dealing with control systems will find the fascinating Neural Systems for Control of immense interest and assistance. Focuses on research in natural and artifical neural systems directly applicable to contol or making use of modern control theory Represents the most up-to-date developments in this rapidly growing application area of neural networks Takes a new and novel approach to system identification and synthesis
Author : E. Colina Morles
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (277 download)
Download or read book Identification and Control of Dynamic Systems Using Neural Networks written by E. Colina Morles and published by . This book was released on 1993 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : George A. Rovithakis
Publisher : Springer Science & Business Media
ISBN 13 : 1447107853
Total Pages : 203 pages
Book Rating : 4.4/5 (471 download)
Download or read book Adaptive Control with Recurrent High-order Neural Networks written by George A. Rovithakis and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 203 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : K. NARENDA
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (143 download)
Download or read book IDENTIFICATION AND CONTROL OF DYNAMICAL SYSTEMS USING NEURAL NETWORKS. written by K. NARENDA and published by . This book was released on with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Cong Wang
Publisher : CRC Press
ISBN 13 : 1420007769
Total Pages : 207 pages
Book Rating : 4.4/5 (2 download)
Download or read book Deterministic Learning Theory for Identification, Recognition, and Control written by Cong Wang and published by CRC Press. This book was released on 2018-10-03 with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deterministic Learning Theory for Identification, Recognition, and Control presents a unified conceptual framework for knowledge acquisition, representation, and knowledge utilization in uncertain dynamic environments. It provides systematic design approaches for identification, recognition, and control of linear uncertain systems. Unlike many books currently available that focus on statistical principles, this book stresses learning through closed-loop neural control, effective representation and recognition of temporal patterns in a deterministic way. A Deterministic View of Learning in Dynamic Environments The authors begin with an introduction to the concepts of deterministic learning theory, followed by a discussion of the persistent excitation property of RBF networks. They describe the elements of deterministic learning, and address dynamical pattern recognition and pattern-based control processes. The results are applicable to areas such as detection and isolation of oscillation faults, ECG/EEG pattern recognition, robot learning and control, and security analysis and control of power systems. A New Model of Information Processing This book elucidates a learning theory which is developed using concepts and tools from the discipline of systems and control. Fundamental knowledge about system dynamics is obtained from dynamical processes, and is then utilized to achieve rapid recognition of dynamical patterns and pattern-based closed-loop control via the so-called internal and dynamical matching of system dynamics. This actually represents a new model of information processing, i.e. a model of dynamical parallel distributed processing (DPDP).
Author : Olawale Adetona
Publisher :
ISBN 13 :
Total Pages : 218 pages
Book Rating : 4.:/5 (396 download)
Download or read book Stable Adaptive Control of Unknown Nonlinear Dynamic Systems Using Neural Networks written by Olawale Adetona and published by . This book was released on 1998 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Yiannis Boutalis
Publisher : Springer Science & Business
ISBN 13 : 3319063642
Total Pages : 316 pages
Book Rating : 4.3/5 (19 download)
Download or read book System Identification and Adaptive Control written by Yiannis Boutalis and published by Springer Science & Business. This book was released on 2014-04-23 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presenting current trends in the development and applications of intelligent systems in engineering, this monograph focuses on recent research results in system identification and control. The recurrent neurofuzzy and the fuzzy cognitive network (FCN) models are presented. Both models are suitable for partially-known or unknown complex time-varying systems. Neurofuzzy Adaptive Control contains rigorous proofs of its statements which result in concrete conclusions for the selection of the design parameters of the algorithms presented. The neurofuzzy model combines concepts from fuzzy systems and recurrent high-order neural networks to produce powerful system approximations that are used for adaptive control. The FCN model stems from fuzzy cognitive maps and uses the notion of “concepts” and their causal relationships to capture the behavior of complex systems. The book shows how, with the benefit of proper training algorithms, these models are potent system emulators suitable for use in engineering systems. All chapters are supported by illustrative simulation experiments, while separate chapters are devoted to the potential industrial applications of each model including projects in: • contemporary power generation; • process control and • conventional benchmarking problems. Researchers and graduate students working in adaptive estimation and intelligent control will find Neurofuzzy Adaptive Control of interest both for the currency of its models and because it demonstrates their relevance for real systems. The monograph also shows industrial engineers how to test intelligent adaptive control easily using proven theoretical results.
Author : Sanjay S. Kumar
Publisher :
ISBN 13 :
Total Pages : 188 pages
Book Rating : 4.:/5 (25 download)
Download or read book Neural Network Based Dynamic System Identification for Adaptive Control written by Sanjay S. Kumar and published by . This book was released on 1989 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Jing Na
Publisher : Academic Press
ISBN 13 : 0128136847
Total Pages : 338 pages
Book Rating : 4.1/5 (281 download)
Download or read book Adaptive Identification and Control of Uncertain Systems with Non-smooth Dynamics written by Jing Na and published by Academic Press. This book was released on 2018-06-12 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive Identification and Control of Uncertain Systems with Nonsmooth Dynamics reports some of the latest research on modeling, identification and adaptive control for systems with nonsmooth dynamics (e.g., backlash, dead zone, friction, saturation, etc). The authors present recent research results for the modelling and control designs of uncertain systems with nonsmooth dynamics, such as friction, dead-zone, saturation and hysteresis, etc., with particular applications in servo systems. The book is organized into 19 chapters, distributed in five parts concerning the four types of nonsmooth characteristics, namely friction, dead-zone, saturation and hysteresis, respectively. Practical experiments are also included to validate and exemplify the proposed approaches. This valuable resource can help both researchers and practitioners to learn and understand nonlinear adaptive control designs. Academics, engineers and graduate students in the fields of electrical engineering, control systems, mechanical engineering, applied mathematics and computer science can benefit from the book. It can be also used as a reference book on adaptive control for servo systems for students with some background in control engineering. Explains the latest research outputs on modeling, identification and adaptive control for systems with nonsmooth dynamics Provides practical application and experimental results for robotic systems, and servo motors
Author : Ssu-Hsin Yu
Publisher :
ISBN 13 :
Total Pages : 160 pages
Book Rating : 4.:/5 (346 download)
Download or read book Model-based Identification and Control of Nonlinear Dynamic Systems Using Neural Networks written by Ssu-Hsin Yu and published by . This book was released on 1996 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Rafa? ?bikowski
Publisher : World Scientific
ISBN 13 : 9789810225575
Total Pages : 368 pages
Book Rating : 4.2/5 (255 download)
Download or read book Neural Adaptive Control Technology written by Rafa? ?bikowski and published by World Scientific. This book was released on 1996 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
