Identification and Adaptive Control for Nonlinear Systems and Applications

Identification and Adaptive Control for Nonlinear Systems and Applications: Applied Mathematics in Control Engineering introduces nonlinear systems concepts, system analysis, system control methods and applications in various fields. The major contribution of the book includes: (1) The basic concepts of nonlinear systems stability analysis and nonlinear systems control method. (2) The stability analysis of complex nonlinear system with adaptive neural networks control. (3) The nonlinear systems adaptive sliding mode controller design of complex nonlinear systems. (4) Some industrial application. The book gives an introduction to basic nonlinear systems architectures for adaptive control methods. Emphasis is placed on the mathematical analysis of these systems, on methods of controlling them for adaptive control and on their application to practical engineering problems in such areas as aircraft path planning. This book enables audience to understand the basic architectures of control science and engineering, and to master classical and advanced design method for nonlinear system. Introduces nonlinear systems concepts, system analysis, system control methods and applications in various fields Presents basic concepts of nonlinear systems stability analysis and nonlinear systems control method Offers practical examples

Produk Detail:

  • Author : Jianhua Zhang
  • Publisher : Academic Press
  • Pages : 320 pages
  • ISBN : 9780128234419
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKIdentification and Adaptive Control for Nonlinear Systems and Applications

Identification and Adaptive Control for Nonlinear Systems and Applications

Identification and Adaptive Control for Nonlinear Systems and Applications
  • Author : Jianhua Zhang,Yang Li,Qiang Chen
  • Publisher : Academic Press
  • Release : 15 March 2022
GET THIS BOOKIdentification and Adaptive Control for Nonlinear Systems and Applications

Identification and Adaptive Control for Nonlinear Systems and Applications: Applied Mathematics in Control Engineering introduces nonlinear systems concepts, system analysis, system control methods and applications in various fields. The major contribution of the book includes: (1) The basic concepts of nonlinear systems stability analysis and nonlinear systems control method. (2) The stability analysis of complex nonlinear system with adaptive neural networks control. (3) The nonlinear systems adaptive sliding mode controller design of complex nonlinear systems. (4) Some industrial application. The book gives an introduction

Nonlinear and Adaptive Control with Applications

Nonlinear and Adaptive Control with Applications
  • Author : Alessandro Astolfi,Dimitrios Karagiannis,Romeo Ortega
  • Publisher : Springer Science & Business Media
  • Release : 06 December 2007
GET THIS BOOKNonlinear and Adaptive Control with Applications

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.

Fuzzy System Identification and Adaptive Control

Fuzzy System Identification and Adaptive Control
  • Author : Ruiyun Qi,Gang Tao,Bin Jiang
  • Publisher : Springer
  • Release : 11 June 2019
GET THIS BOOKFuzzy System Identification and Adaptive Control

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

Learning-Based Adaptive Control

Learning-Based Adaptive Control
  • Author : Mouhacine Benosman
  • Publisher : Butterworth-Heinemann
  • Release : 02 August 2016
GET THIS BOOKLearning-Based Adaptive Control

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

Adaptive Nonlinear System Identification

Adaptive Nonlinear System Identification
  • Author : Tokunbo Ogunfunmi
  • Publisher : Springer Science & Business Media
  • Release : 05 September 2007
GET THIS BOOKAdaptive Nonlinear System Identification

Focuses on System Identification applications of the adaptive methods presented. but which can also be applied to other applications of adaptive nonlinear processes. Covers recent research results in the area of adaptive nonlinear system identification from the authors and other researchers in the field.

System Identification and Adaptive Control

System Identification and Adaptive Control
  • Author : Yiannis Boutalis,Dimitrios Theodoridis,Theodore Kottas,Manolis A. Christodoulou
  • Publisher : Springer Science & Business
  • Release : 23 April 2014
GET THIS BOOKSystem Identification and Adaptive Control

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

Digital Control Systems

Digital Control Systems
  • Author : Ioan Doré Landau,Gianluca Zito
  • Publisher : Springer
  • Release : 19 October 2010
GET THIS BOOKDigital Control Systems

The extraordinary development of digital computers (microprocessors, microcontrollers) and their extensive use in control systems in all fields of applications has brought about important changes in the design of control systems. Their performance and their low cost make them suitable for use in control systems of various kinds which demand far better capabilities and performances than those provided by analog controllers. However, in order really to take advantage of the capabilities of microprocessors, it is not enough to reproduce the

Neural Network-Based Adaptive Control of Uncertain Nonlinear Systems

Neural Network-Based Adaptive Control of Uncertain Nonlinear Systems
  • Author : Kasra Esfandiari,Farzaneh Abdollahi,Heidar A. Talebi
  • Publisher : Springer Nature
  • Release : 20 July 2021
GET THIS BOOKNeural Network-Based Adaptive Control of Uncertain Nonlinear Systems

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

Adaptive Learning Methods for Nonlinear System Modeling

Adaptive Learning Methods for Nonlinear System Modeling
  • Author : Danilo Comminiello,Jose C. Principe
  • Publisher : Butterworth-Heinemann
  • Release : 11 June 2018
GET THIS BOOKAdaptive Learning Methods for Nonlinear System Modeling

Adaptive Learning Methods for Nonlinear System Modeling presents some of the recent advances on adaptive algorithms and machine learning methods designed for nonlinear system modeling and identification. Real-life problems always entail a certain degree of nonlinearity, which makes linear models a non-optimal choice. This book mainly focuses on those methodologies for nonlinear modeling that involve any adaptive learning approaches to process data coming from an unknown nonlinear system. By learning from available data, such methods aim at estimating the nonlinearity

Adaptive Sliding Mode Neural Network Control for Nonlinear Systems

Adaptive Sliding Mode Neural Network Control for Nonlinear Systems
  • Author : Yang Li,Jianhua Zhang,Wu Qiong
  • Publisher : Academic Press
  • Release : 16 November 2018
GET THIS BOOKAdaptive Sliding Mode Neural Network Control for Nonlinear Systems

Adaptive Sliding Mode Neural Network Control for Nonlinear Systems introduces nonlinear systems basic knowledge, analysis and control methods, and applications in various fields. It offers instructive examples and simulations, along with the source codes, and provides the basic architecture of control science and engineering. Introduces nonlinear systems' basic knowledge, analysis and control methods, along with applications in various fields Offers instructive examples and simulations, including source codes Provides the basic architecture of control science and engineering

Advances and Applications in Nonlinear Control Systems

Advances and Applications in Nonlinear Control Systems
  • Author : Sundarapandian Vaidyanathan,Christos Volos
  • Publisher : Springer
  • Release : 17 March 2016
GET THIS BOOKAdvances and Applications in Nonlinear Control Systems

The book reports on the latest advances and applications of nonlinear control systems. It consists of 30 contributed chapters by subject experts who are specialized in the various topics addressed in this book. The special chapters have been brought out in the broad areas of nonlinear control systems such as robotics, nonlinear circuits, power systems, memristors, underwater vehicles, chemical processes, observer design, output regulation, backstepping control, sliding mode control, time-delayed control, variables structure control, robust adaptive control, fuzzy logic control, chaos,

Adaptive Systems in Control and Signal Processing 1992

Adaptive Systems in Control and Signal Processing 1992
  • Author : L. Dugard,M. M'Saad,I.D. Landau
  • Publisher : Elsevier
  • Release : 28 June 2014
GET THIS BOOKAdaptive Systems in Control and Signal Processing 1992

Adaptive Systems remain a very interesting field of theoretical research, extended by methodological studies and an increasing number of applications. The plenary papers, invited sessions and contributed sessions focused on many aspects of adaptive systems, such as systems identification and modelling, adaptive control of nonlinear systems and theoretical issues in adaptive control. Also covered were methodological aspects and applications of adaptive control, intelligent tuning and adaptive signal processing.

Nonlinear Identification and Adaptive Control

Nonlinear Identification and Adaptive Control
  • Author : Anonim
  • Publisher : Unknown Publisher
  • Release : 22 September 2021
GET THIS BOOKNonlinear Identification and Adaptive Control

To address Air Force applications, new methods are developed for system identification (ID) and adaptive control. For linear systems, ID algorithms are developed to obtain consistent parameter estimates, stable models, and optimal inputs. Nonlinear ID methods are developed for block-structured models with measured-input nonlinearities. Subspace ID methods are used to identify linear model components, while optimization methods are used to construct efficient basis functions. Specialized methods are developed to identify nonlinear systems with output nonlinearities, limit cycle dynamics, and hysteresis.

Intelligent Components and Instruments for Control Applications 1994

Intelligent Components and Instruments for Control Applications 1994
  • Author : Cs. Banyasz
  • Publisher : Elsevier
  • Release : 23 May 2014
GET THIS BOOKIntelligent Components and Instruments for Control Applications 1994

Advances in computer technology and sensor development have led to increasingly successful control operations. In order to maximize future potential it is vital for academics and practitioners in the field to have an international forum for discussion and evaluation of the latest developments. The IFAC Symposia on intelligent components and instruments provide this opportunity and the latest in the series gives rise to this invaluable publication which provides an authoritative assessment of the present state and future directions of these