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Author: Ruiyun Qi
Publisher: Springer
ISBN: 3030198820
Category : Technology & Engineering
Languages : en
Pages : 282
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Book Description
This book provides readers with a systematic and unified framework for identification and adaptive control of Takagi–Sugeno (T–S) fuzzy systems. Its design techniques help readers applying these powerful tools to solve challenging nonlinear control problems. The book embodies a systematic study of fuzzy system identification and control problems, using T–S fuzzy system tools for both function approximation and feedback control of nonlinear systems. Alongside this framework, the book also: introduces basic concepts of fuzzy sets, logic and inference system; discusses important properties of T–S fuzzy systems; develops offline and online identification algorithms for T–S fuzzy systems; investigates the various controller structures and corresponding design conditions for adaptive control of continuous-time T–S fuzzy systems; develops adaptive control algorithms for discrete-time input–output form T–S fuzzy systems with much relaxed design conditions, and discrete-time state-space T–S fuzzy systems; and designs stable parameter-adaptation algorithms for both linearly and nonlinearly parameterized T–S fuzzy systems. The authors address adaptive fault compensation problems for T–S fuzzy systems subject to actuator faults. They cover a broad spectrum of related technical topics and to develop a substantial set of adaptive nonlinear system control tools. Fuzzy System Identification and Adaptive Control helps engineers in the mechanical, electrical and aerospace fields, to solve complex control design problems. The book can be used as a reference for researchers and academics in nonlinear, intelligent, adaptive and fault-tolerant control.
Author: Ruiyun Qi
Publisher: Springer
ISBN: 3030198820
Category : Technology & Engineering
Languages : en
Pages : 282
Get Book
Book Description
This book provides readers with a systematic and unified framework for identification and adaptive control of Takagi–Sugeno (T–S) fuzzy systems. Its design techniques help readers applying these powerful tools to solve challenging nonlinear control problems. The book embodies a systematic study of fuzzy system identification and control problems, using T–S fuzzy system tools for both function approximation and feedback control of nonlinear systems. Alongside this framework, the book also: introduces basic concepts of fuzzy sets, logic and inference system; discusses important properties of T–S fuzzy systems; develops offline and online identification algorithms for T–S fuzzy systems; investigates the various controller structures and corresponding design conditions for adaptive control of continuous-time T–S fuzzy systems; develops adaptive control algorithms for discrete-time input–output form T–S fuzzy systems with much relaxed design conditions, and discrete-time state-space T–S fuzzy systems; and designs stable parameter-adaptation algorithms for both linearly and nonlinearly parameterized T–S fuzzy systems. The authors address adaptive fault compensation problems for T–S fuzzy systems subject to actuator faults. They cover a broad spectrum of related technical topics and to develop a substantial set of adaptive nonlinear system control tools. Fuzzy System Identification and Adaptive Control helps engineers in the mechanical, electrical and aerospace fields, to solve complex control design problems. The book can be used as a reference for researchers and academics in nonlinear, intelligent, adaptive and fault-tolerant control.
Author: Ruiyun Qi
Publisher:
ISBN: 9783030198831
Category : Artificial intelligence
Languages : en
Pages : 282
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Book Description
This book provides readers with a systematic and unified framework for identification and adaptive control of Takagi-Sugeno (T-S) fuzzy systems. Its design techniques help readers applying these powerful tools to solve challenging nonlinear control problems. The book embodies a systematic study of fuzzy system identification and control problems, using T-S fuzzy system tools for both function approximation and feedback control of nonlinear systems. Alongside this framework, the book also: introduces basic concepts of fuzzy sets, logic and inference system; discusses important properties of T-S fuzzy systems; develops offline and online identification algorithms for T-S fuzzy systems; investigates the various controller structures and corresponding design conditions for adaptive control of continuous-time T-S fuzzy systems; develops adaptive control algorithms for discrete-time input-output form T-S fuzzy systems with much relaxed design conditions, and discrete-time state-space T-S fuzzy systems; and designs stable parameter-adaptation algorithms for both linearly and nonlinearly parameterized T-S fuzzy systems. The authors address adaptive fault compensation problems for T-S fuzzy systems subject to actuator faults. They cover a broad spectrum of related technical topics and to develop a substantial set of adaptive nonlinear system control tools. Fuzzy System Identification and Adaptive Control helps engineers in the mechanical, electrical and aerospace fields, to solve complex control design problems. The book can be used as a reference for researchers and academics in nonlinear, intelligent, adaptive and fault-tolerant control.
Author: Yiannis Boutalis
Publisher: Springer Science & Business
ISBN: 3319063642
Category : Technology & Engineering
Languages : en
Pages : 313
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Book Description
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: John H. Lilly
Publisher: John Wiley & Sons
ISBN: 9781118097816
Category : Technology & Engineering
Languages : en
Pages : 248
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Book Description
This book gives an introduction to basic fuzzy logic and Mamdaniand Takagi-Sugeno fuzzy systems. The text shows howthese can be used to control complex nonlinear engineering systems,while also also suggesting several approaches to modelingof complex engineering systems with unknown models. Finally, fuzzy modeling and control methods are combined in thebook, to create adaptive fuzzy controllers, ending withan example of an obstacle-avoidance controller for an autonomousvehicle using modus ponendo tollens logic.
Author: Li-Xin Wang
Publisher: Prentice Hall
ISBN:
Category : Computers
Languages : en
Pages : 262
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Book Description
This volume develops a variety of adaptive fuzzy systems and applies them to a variety of engineering problems. It summarizes the state-of-the-art methods for automatic tuning of the parameters and structures of fuzzy logic systems.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
HKUST Call Number: Thesis ELEC 2001 Wan.
Author: Janos Abonyi
Publisher: Springer Science & Business Media
ISBN: 146120027X
Category : Technology & Engineering
Languages : en
Pages : 279
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Book Description
This book presents new approaches to constructing fuzzy models for model-based control. Simulated examples and real-world applications from chemical and process engineering illustrate the main methods and techniques. Supporting MATLAB and Simulink files create a computational platform for exploration of the concepts and algorithms.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Jairo Jose Espinosa Oviedo
Publisher: Springer Science & Business Media
ISBN: 1846280877
Category : Technology & Engineering
Languages : en
Pages : 274
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Book Description
Modern industrial processes and systems require adaptable advanced control protocols able to deal with circumstances demanding "judgement” rather than simple "yes/no”, "on/off” responses: circumstances where a linguistic description is often more relevant than a cut-and-dried numerical one. The ability of fuzzy systems to handle numeric and linguistic information within a single framework renders them efficacious for this purpose. Fuzzy Logic, Identification and Predictive Control first shows you how to construct static and dynamic fuzzy models using the numerical data from a variety of real industrial systems and simulations. The second part exploits such models to design control systems employing techniques like data mining. This monograph presents a combination of fuzzy control theory and industrial serviceability that will make a telling contribution to your research whether in the academic or industrial sphere and also serves as a fine roundup of the fuzzy control area for the graduate student.
Author: Dr. SHAIK RAFI KIRAN
Publisher: Lulu.com
ISBN: 1329937201
Category :
Languages : en
Pages : 118
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Book Description
