Model Free Adaptive Control

Model Free Adaptive Control
Author: Zhongsheng Hou
Publisher: CRC Press
Total Pages: 400
Release: 2013-09-24
Genre: Technology & Engineering
ISBN: 1466594187

Model Free Adaptive Control: Theory and Applications summarizes theory and applications of model-free adaptive control (MFAC). MFAC is a novel adaptive control method for the unknown discrete-time nonlinear systems with time-varying parameters and time-varying structure, and the design and analysis of MFAC merely depend on the measured input and output data of the controlled plant, which makes it more applicable for many practical plants. This book covers new concepts, including pseudo partial derivative, pseudo gradient, pseudo Jacobian matrix, and generalized Lipschitz conditions, etc.; dynamic linearization approaches for nonlinear systems, such as compact-form dynamic linearization, partial-form dynamic linearization, and full-form dynamic linearization; a series of control system design methods, including MFAC prototype, model-free adaptive predictive control, model-free adaptive iterative learning control, and the corresponding stability analysis and typical applications in practice. In addition, some other important issues related to MFAC are also discussed. They are the MFAC for complex connected systems, the modularized controller designs between MFAC and other control methods, the robustness of MFAC, and the symmetric similarity for adaptive control system design. The book is written for researchers who are interested in control theory and control engineering, senior undergraduates and graduated students in engineering and applied sciences, as well as professional engineers in process control.

Model-Reference Adaptive Control

Model-Reference Adaptive Control
Author: Nhan T. Nguyen
Publisher: Springer
Total Pages: 453
Release: 2018-03-01
Genre: Technology & Engineering
ISBN: 3319563939

This textbook provides readers with a good working knowledge of adaptive control theory through applications. It is intended for students beginning masters or doctoral courses, and control practitioners wishing to get up to speed in the subject expeditiously. Readers are taught a wide variety of adaptive control techniques starting with simple methods and extending step-by-step to more complex ones. Stability proofs are provided for all adaptive control techniques without obfuscating reader understanding with excessive mathematics. The book begins with standard model-reference adaptive control (MRAC) for first-order, second-order, and multi-input, multi-output systems. Treatment of least-squares parameter estimation and its extension to MRAC follow, helping readers to gain a different perspective on MRAC. Function approximation with orthogonal polynomials and neural networks, and MRAC using neural networks are also covered. Robustness issues connected with MRAC are discussed, helping the student to appreciate potential pitfalls of the technique. This appreciation is encouraged by drawing parallels between various aspects of robustness and linear time-invariant systems wherever relevant. Following on from the robustness problems is material covering robust adaptive control including standard methods and detailed exposition of recent advances, in particular, the author’s work on optimal control modification. Interesting properties of the new method are illustrated in the design of adaptive systems to meet stability margins. This method has been successfully flight-tested on research aircraft, one of various flight-control applications detailed towards the end of the book along with a hybrid adaptive flight control architecture that combines direct MRAC with least-squares indirect adaptive control. In addition to the applications, understanding is encouraged by the use of end-of-chapter exercises and associated MATLAB® files. Readers will need no more than the standard mathematics for basic control theory such as differential equations and matrix algebra; the book covers the foundations of MRAC and the necessary mathematical preliminaries.

Learning-Based Adaptive Control

Learning-Based Adaptive Control
Author: Mouhacine Benosman
Publisher: Butterworth-Heinemann
Total Pages: 284
Release: 2016-08-02
Genre: Technology & Engineering
ISBN: 0128031514

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.

Robust Adaptive Control

Robust Adaptive Control
Author: Petros Ioannou
Publisher: Courier Corporation
Total Pages: 850
Release: 2013-09-26
Genre: Technology & Engineering
ISBN: 0486320723

Presented in a tutorial style, this comprehensive treatment unifies, simplifies, and explains most of the techniques for designing and analyzing adaptive control systems. Numerous examples clarify procedures and methods. 1995 edition.

Adaptive Internal Model Control

Adaptive Internal Model Control
Author: Aniruddha Datta
Publisher: Springer Science & Business Media
Total Pages: 166
Release: 2012-12-06
Genre: Technology & Engineering
ISBN: 0857293311

Written in a self-contained tutorial fashion, this monograph successfully brings the latest theoretical advances in the design of robust adaptive systems to the realm of industrial applications. It provides a theoretical basis for verifying some of the reported industrial successes of existing adaptive control schemes and enables readers to synthesize adaptive versions of their own robust internal model control schemes.

Techniques for Adaptive Control

Techniques for Adaptive Control
Author: Vance J. VanDoren
Publisher: Butterworth-Heinemann
Total Pages: 290
Release: 2003
Genre: Business & Economics
ISBN:

Adaptive Tuning Methods of the Foxboro I/A System; The Exploitation of Adaptive Modelling in the Model Predictive Control Environment of Connoisseur; Adaptive Predictive Regulatory Control with BrainWave; Model-Free Adaptive Control; Expert-Based Adaptive Control -- ControlSoft's INTUNE Adaptive and Diagnostic Software; KnowledgeScape, an Object-oriented Real-time Adaptive Modeling and Optimization Expert Control System for the Process Industries.

Adaptive Control of Systems with Actuator Failures

Adaptive Control of Systems with Actuator Failures
Author: Gang Tao
Publisher: Springer Science & Business Media
Total Pages: 324
Release: 2004-04-02
Genre: Science
ISBN: 9781852337889

This book shows readers new ways to compensate for disturbances in control systems prolonging the intervals between time-consuming and/or expensive fault diagnosis procedures, keeping them up to date in the increasingly important field of adaptive control.

System Identification and Adaptive Control

System Identification and Adaptive Control
Author: Yiannis Boutalis
Publisher: Springer Science & Business
Total Pages: 316
Release: 2014-04-23
Genre: Technology & Engineering
ISBN: 3319063642

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.

Functional Adaptive Control

Functional Adaptive Control
Author: Simon G. Fabri
Publisher: Springer Science & Business Media
Total Pages: 275
Release: 2012-12-06
Genre: Technology & Engineering
ISBN: 144710319X

Unique in its systematic approach to stochastic systems, this book presents a wide range of techniques that lead to novel strategies for effecting intelligent control of complex systems that are typically characterised by uncertainty, nonlinear dynamics, component failure, unpredictable disturbances, multi-modality and high dimensional spaces.

Adaptive Control Tutorial

Adaptive Control Tutorial
Author: Petros Ioannou
Publisher: SIAM
Total Pages: 401
Release: 2006-01-01
Genre: Mathematics
ISBN: 0898716152

Designed to meet the needs of a wide audience without sacrificing mathematical depth and rigor, Adaptive Control Tutorial presents the design, analysis, and application of a wide variety of algorithms that can be used to manage dynamical systems with unknown parameters. Its tutorial-style presentation of the fundamental techniques and algorithms in adaptive control make it suitable as a textbook. Adaptive Control Tutorial is designed to serve the needs of three distinct groups of readers: engineers and students interested in learning how to design, simulate, and implement parameter estimators and adaptive control schemes without having to fully understand the analytical and technical proofs; graduate students who, in addition to attaining the aforementioned objectives, also want to understand the analysis of simple schemes and get an idea of the steps involved in more complex proofs; and advanced students and researchers who want to study and understand the details of long and technical proofs with an eye toward pursuing research in adaptive control or related topics. The authors achieve these multiple objectives by enriching the book with examples demonstrating the design procedures and basic analysis steps and by detailing their proofs in both an appendix and electronically available supplementary material; online examples are also available. A solution manual for instructors can be obtained by contacting SIAM or the authors. Preface; Acknowledgements; List of Acronyms; Chapter 1: Introduction; Chapter 2: Parametric Models; Chapter 3: Parameter Identification: Continuous Time; Chapter 4: Parameter Identification: Discrete Time; Chapter 5: Continuous-Time Model Reference Adaptive Control; Chapter 6: Continuous-Time Adaptive Pole Placement Control; Chapter 7: Adaptive Control for Discrete-Time Systems; Chapter 8: Adaptive Control of Nonlinear Systems; Appendix; Bibliography; Index