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Author: Cong Wang
Publisher: CRC Press
ISBN: 1420007769
Category : Technology & Engineering
Languages : en
Pages : 207
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Book Description
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: Cong Wang
Publisher: CRC Press
ISBN: 1420007769
Category : Technology & Engineering
Languages : en
Pages : 207
Get Book Here
Book Description
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: George D. Magoulas
Publisher: IGI Global
ISBN: 1466638915
Category : Computers
Languages : en
Pages : 351
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Book Description
"This book provides original research on the theoretical and applied aspects of artificial life, as well as addresses scientific, psychological, and social issues of synthetic life-like behavior and abilities"--Provided by publisher.
Author: Yingmin Jia
Publisher: Springer
ISBN: 9811322910
Category : Technology & Engineering
Languages : en
Pages : 844
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Book Description
These proceedings present selected research papers from CISC’18, held in Wenzhou, China. The topics include Multi-Agent Systems, Networked Control Systems, Intelligent Robots, Complex System Theory and Swarm Behavior, Event-Triggered Control and Data-Driven Control, Robust and Adaptive Control, Big Data and Brain Science, Process Control, Nonlinear and Variable Structure Control, Intelligent Sensor and Detection Technology, Deep learning and Learning Control Guidance, Navigation and Control of Flight Vehicles, and so on. Engineers and researchers from academia, industry, and government can get an insight view of the solutions combining ideas from multiple disciplines in the field of intelligent systems.
Author: Yong-Duan Song
Publisher: CRC Press
ISBN: 0429847637
Category : Technology & Engineering
Languages : en
Pages : 216
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Book Description
The purpose of this book is to give an exposition of recently adaptive PI/PD/PID control design for nonlinear systems. Since PI/PD/PID control is simple in structure and inexpensive in implementation, it has been undoubtedly the most widely employed controller in industry. In fact, PI/PD/PID controllers are sufficient for many control problems, particularly when process dynamics are benign and the performance requirements are modest. The book focuses on how to design general PI/PD/PID controller with self-tuning gains for different systems, which includes SISO nonlinear system, SISO nonaffine system and MIMO nonlinear system.
Author: Derong Liu
Publisher: Springer
ISBN: 3642387861
Category : Computers
Languages : en
Pages : 429
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Book Description
This book constitutes the refereed proceedings of the 6th International Conference on Brain Inspired Cognitive Systems, BICS 2013, held in Beijing, China in June 2013. The 45 high-quality papers presented were carefully reviewed and selected from 68 submissions. BICS 2013 aims to provide a high-level international forum for scientists, engineers, and educators to present the state of the art of brain inspired cognitive systems research and applications in diverse fields.
Author: Mouhacine Benosman
Publisher: Butterworth-Heinemann
ISBN: 0128031514
Category : Technology & Engineering
Languages : en
Pages : 284
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Book Description
Adaptive control has been one of the main problems studied in control theory. The subject is well understood, yet it has a very active research frontier. This book focuses on a specific subclass of adaptive control, namely, learning-based adaptive control. As systems evolve during time or are exposed to unstructured environments, it is expected that some of their characteristics may change. This book offers a new perspective about how to deal with these variations. By merging together Model-Free and Model-Based learning algorithms, the author demonstrates, using a number of mechatronic examples, how the learning process can be shortened and optimal control performance can be reached and maintained. - Includes a good number of Mechatronics Examples of the techniques. - Compares and blends Model-free and Model-based learning algorithms. - Covers fundamental concepts, state-of-the-art research, necessary tools for modeling, and control.
Author: Wei He
Publisher: Springer
ISBN: 9811075395
Category : Technology & Engineering
Languages : en
Pages : 202
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Book Description
This book presents theoretical explorations of several fundamental problems in the dynamics and control of flexible beam systems. By integrating fresh concepts and results to form a systematic approach to control, it establishes a basic theoretical framework. It includes typical control design examples verified using MATLAB simulation, which in turn illustrate the successful practical applications of active vibration control theory for flexible beam systems. The book is primarily intended for researchers and engineers in the control system and mechanical engineering community, offering them a unique resource.
Author: Edgar N. Sanchez
Publisher: CRC Press
ISBN: 1351377434
Category : Technology & Engineering
Languages : en
Pages : 292
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Book Description
The book presents recent advances in the theory of neural control for discrete-time nonlinear systems with multiple inputs and multiple outputs. The simulation results that appear in each chapter include rigorous mathematical analyses, based on the Lyapunov approach, to establish its properties. The book contains two sections: the first focuses on the analyses of control techniques; the second is dedicated to illustrating results of real-time applications. It also provides solutions for the output trajectory tracking problem of unknown nonlinear systems based on sliding modes and inverse optimal control scheme. "This book on Discrete-time Recurrent Neural Control is unique in the literature, with new knowledge and information about the new technique of recurrent neural control especially for discrete-time systems. The book is well organized and clearly presented. It will be welcome by a wide range of researchers in science and engineering, especially graduate students and junior researchers who want to learn the new notion of recurrent neural control. I believe it will have a good market. It is an excellent book after all." — Guanrong Chen, City University of Hong Kong "This book includes very relevant topics, about neural control. In these days, Artificial Neural Networks have been recovering their relevance and well-stablished importance, this due to its great capacity to process big amounts of data. Artificial Neural Networks development always is related to technological advancements; therefore, it is not a surprise that now we are being witnesses of this new era in Artificial Neural Networks, however most of the developments in this research area only focuses on applicability of the proposed schemes. However, Edgar N. Sanchez author of this book does not lose focus and include both important applications as well as a deep theoretical analysis of Artificial Neural Networks to control discrete-time nonlinear systems. It is important to remark that first, the considered Artificial Neural Networks are development in discrete-time this simplify its implementation in real-time; secondly, the proposed applications ranging from modelling of unknown discrete-time on linear systems to control electrical machines with an emphasize to renewable energy systems. However, its applications are not limited to these kind of systems, due to their theoretical foundation it can be applicable to a large class of nonlinear systems. All of these is supported by the solid research done by the author." — Alma Y. Alanis, University of Guadalajara, Mexico "This book discusses in detail; how neural networks can be used for optimal as well as robust control design. Design of neural network controllers for real time applications such as induction motors, boost converters, inverted pendulum and doubly fed induction generators has also been carried out which gives the book an edge over other similar titles. This book will be an asset for the novice to the experienced ones." — Rajesh Joseph Abraham, Indian Institute of Space Science & Technology, Thiruvananthapuram, India
Author: Yingmin Jia
Publisher: Springer Nature
ISBN: 9819786509
Category :
Languages : en
Pages : 687
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Book Description
Author: Constantine H. Houpis
Publisher: CRC Press
ISBN: 1466504269
Category : Technology & Engineering
Languages : en
Pages : 732
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Book Description
Thoroughly classroom-tested and proven to be a valuable self-study companion, Linear Control System Analysis and Design: Sixth Edition provides an intensive overview of modern control theory and conventional control system design using in-depth explanations, diagrams, calculations, and tables. Keeping mathematics to a minimum, the book is designed with the undergraduate in mind, first building a foundation, then bridging the gap between control theory and its real-world application. Computer-aided design accuracy checks (CADAC) are used throughout the text to enhance computer literacy. Each CADAC uses fundamental concepts to ensure the viability of a computer solution. Completely updated and packed with student-friendly features, the sixth edition presents a range of updated examples using MATLAB®, as well as an appendix listing MATLAB functions for optimizing control system analysis and design. Over 75 percent of the problems presented in the previous edition have been revised or replaced.
