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Virtual equivalent system approach f...

Li, Qing.

Virtual equivalent system approach for stability analysis of model-based control systems

Record Type:	Electronic resources : Monograph/item
Title/Author:	Virtual equivalent system approach for stability analysis of model-based control systemsby Weicun Zhang, Qing Li.
Author:	Zhang, Weicun.
other author:	Li, Qing.
Published:	Singapore :Springer Singapore :2021.
Description:	xiii, 168 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Predictive control.
Online resource:	https://doi.org/10.1007/978-981-15-5538-1
ISBN:	9789811555381$q(electronic bk.)

Virtual equivalent system approach for stability analysis of model-based control systems
Zhang, Weicun.

Virtual equivalent system approach for stability analysis of model-based control systems[electronic resource] /by Weicun Zhang, Qing Li. - Singapore :Springer Singapore :2021. - xiii, 168 p. :ill., digital ;24 cm.

Motivation and Contents of the Monograph -- Stability and Convergence Analysis of Self-Tuning Control Systems -- Further Results On Stability and Convergence of Self-Tuning Control Systems -- Stable Weighted Multiple Model Adaptive Control: Continuous-Time Plant -- Stable Weighted Multiple Model Adaptive Control: Discrete-Time Stochastic Plant -- Further Results on Stable Weighted Multiple Model Adaptive Control: Discrete-Time Stochastic Plant -- Stability of Continuous-Time T-S Model Based Fuzzy Control Systems -- Appendix A Lemma and proofs for Chapter 2 -- Appendix B Lemma and Proofs for Chapter 4 -- Appendix C Lemma and proofs for Chapter 6 -- Appendix D Lemma and proofs for Chapter 7.

This book puts forward the concept of a virtual equivalent system (VES) based on theoretical analysis and simulation results. The new concept will facilitate the development of a uniﬁed framework for analyzing the stability and convergence of self-tuning control (STC) systems, and potentially, of all adaptive control systems. The book then shows that a time-varying STC system can be converted into a time-invariant system using a certain nonlinear compensation signal, which reduces the complexity and diﬃculty of stability and convergence analysis. In closing, the VES concept and methodology are used to assess the stability of multiple model adaptive control (MMAC) systems and T-S model-based fuzzy control systems.

ISBN: 9789811555381$q(electronic bk.)

Standard No.: 10.1007/978-981-15-5538-1doiSubjects--Topical Terms:

182316
Predictive control.

LC Class. No.: TJ217.6 / .Z43 2021

Dewey Class. No.: 629.1326

Virtual equivalent system approach for stability analysis of model-based control systems
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245 1 0 $a Virtual equivalent system approach for stability analysis of model-based control systems $h [electronic resource] / $c by Weicun Zhang, Qing Li.
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505 0 $a Motivation and Contents of the Monograph -- Stability and Convergence Analysis of Self-Tuning Control Systems -- Further Results On Stability and Convergence of Self-Tuning Control Systems -- Stable Weighted Multiple Model Adaptive Control: Continuous-Time Plant -- Stable Weighted Multiple Model Adaptive Control: Discrete-Time Stochastic Plant -- Further Results on Stable Weighted Multiple Model Adaptive Control: Discrete-Time Stochastic Plant -- Stability of Continuous-Time T-S Model Based Fuzzy Control Systems -- Appendix A Lemma and proofs for Chapter 2 -- Appendix B Lemma and Proofs for Chapter 4 -- Appendix C Lemma and proofs for Chapter 6 -- Appendix D Lemma and proofs for Chapter 7.
520 $a This book puts forward the concept of a virtual equivalent system (VES) based on theoretical analysis and simulation results. The new concept will facilitate the development of a uniﬁed framework for analyzing the stability and convergence of self-tuning control (STC) systems, and potentially, of all adaptive control systems. The book then shows that a time-varying STC system can be converted into a time-invariant system using a certain nonlinear compensation signal, which reduces the complexity and diﬃculty of stability and convergence analysis. In closing, the VES concept and methodology are used to assess the stability of multiple model adaptive control (MMAC) systems and T-S model-based fuzzy control systems.
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