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Adaptive Estimation And Control
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Book Synopsis Adaptive Estimation and Control by : Marc Bodson
Download or read book Adaptive Estimation and Control written by Marc Bodson and published by . This book was released on 2020-08-16 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: The objective of this book is to present an introduction to adaptive estimation and control suitable for a graduate-level course or for self-study. Most of the theory is developed in continuous-time, but discrete-time algorithms are also given and yield more direct implementations. Examples and applications are provided to illustrate the results. The book is designed to be accessible with little knowledge beyond an introductory course on feedback control. Background material is included when appropriate. In addition to introducing the reader to adaptive estimation and control algorithms, the text provides many opportunities to apply knowledge of matrix analysis and systems theory in a meaningful context.
Book Synopsis On-line Estimation and Adaptive Control of Bioreactors by : G. Bastin
Download or read book On-line Estimation and Adaptive Control of Bioreactors written by G. Bastin and published by Elsevier. This book was released on 2013-10-22 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book deals with monitoring and control of biotechnological processes. Different methods are proposed which are based on the nonlinear structure of the process and do not require any a priori knowledge of the fermentation parameters. The theoretical stability and convergence properties of the proposed algorithms are analysed and their performances are illustrated by simulation results and, in many instances, by real life experiments. The concept of software sensors is introduced; these are algorithms based on the nonlinear model of the process and designed for on-line estimation of the biological variables and/or the fermentation parameters. In order to deal with process nonstationarities and parameter uncertainties, reference is made to adaptive estimation and control techniques.The book is the result of an intensive joint research effort by the authors during the last decade. It is intended as a graduate level text for students of bioengineering as well as a reference text for scientists and engineers involved in the design and optimization of bioprocesses.
Book Synopsis Stable Adaptive Control and Estimation for Nonlinear Systems by : Jeffrey T. Spooner
Download or read book Stable Adaptive Control and Estimation for Nonlinear Systems written by Jeffrey T. Spooner and published by John Wiley & Sons. This book was released on 2004-04-07 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: Thema dieses Buches ist die Anwendung neuronaler Netze und Fuzzy-Logic-Methoden zur Identifikation und Steuerung nichtlinear-dynamischer Systeme. Dabei werden fortgeschrittene Konzepte der herkömmlichen Steuerungstheorie mit den intuitiven Eigenschaften intelligenter Systeme kombiniert, um praxisrelevante Steuerungsaufgaben zu lösen. Die Autoren bieten viel Hintergrundmaterial; ausgearbeitete Beispiele und Übungsaufgaben helfen Studenten und Praktikern beim Vertiefen des Stoffes. Lösungen zu den Aufgaben sowie MATLAB-Codebeispiele sind ebenfalls enthalten.
Book Synopsis Adaptive Control Design and Analysis by : Gang Tao
Download or read book Adaptive Control Design and Analysis written by Gang Tao and published by John Wiley & Sons. This book was released on 2003-07-09 with total page 652 pages. Available in PDF, EPUB and Kindle. Book excerpt: A systematic and unified presentation of the fundamentals of adaptive control theory in both continuous time and discrete time Today, adaptive control theory has grown to be a rigorous and mature discipline. As the advantages of adaptive systems for developing advanced applications grow apparent, adaptive control is becoming more popular in many fields of engineering and science. Using a simple, balanced, and harmonious style, this book provides a convenient introduction to the subject and improves one's understanding of adaptive control theory. Adaptive Control Design and Analysis features: Introduction to systems and control Stability, operator norms, and signal convergence Adaptive parameter estimation State feedback adaptive control designs Parametrization of state observers for adaptive control Unified continuous and discrete-time adaptive control L1+a robustness theory for adaptive systems Direct and indirect adaptive control designs Benchmark comparison study of adaptive control designs Multivariate adaptive control Nonlinear adaptive control Adaptive compensation of actuator nonlinearities End-of-chapter discussion, problems, and advanced topics As either a textbook or reference, this self-contained tutorial of adaptive control design and analysis is ideal for practicing engineers, researchers, and graduate students alike.
Book Synopsis Robust Adaptive Control by : Petros Ioannou
Download or read book Robust Adaptive Control written by Petros Ioannou and published by Courier Corporation. This book was released on 2013-09-26 with total page 850 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Stochastic Systems written by P. R. Kumar and published by SIAM. This book was released on 2015-12-15 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since its origins in the 1940s, the subject of decision making under uncertainty has grown into a diversified area with application in several branches of engineering and in those areas of the social sciences concerned with policy analysis and prescription. These approaches required a computing capacity too expensive for the time, until the ability to collect and process huge quantities of data engendered an explosion of work in the area. This book provides succinct and rigorous treatment of the foundations of stochastic control; a unified approach to filtering, estimation, prediction, and stochastic and adaptive control; and the conceptual framework necessary to understand current trends in stochastic control, data mining, machine learning, and robotics.
Book Synopsis Adaptive Filtering Prediction and Control by : Graham C Goodwin
Download or read book Adaptive Filtering Prediction and Control written by Graham C Goodwin and published by Courier Corporation. This book was released on 2014-05-05 with total page 562 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unified survey focuses on linear discrete-time systems and explores natural extensions to nonlinear systems. It emphasizes discrete-time systems, summarizing theoretical and practical aspects of a large class of adaptive algorithms. 1984 edition.
Book Synopsis Adaptive Control by : Karl J. Åström
Download or read book Adaptive Control written by Karl J. Åström and published by Courier Corporation. This book was released on 2013-04-26 with total page 596 pages. Available in PDF, EPUB and Kindle. Book excerpt: Suitable for advanced undergraduates and graduate students, this overview introduces theoretical and practical aspects of adaptive control, with emphasis on deterministic and stochastic viewpoints. 1995 edition.
Book Synopsis Identification and Stochastic Adaptive Control by : Han-fu Chen
Download or read book Identification and Stochastic Adaptive Control written by Han-fu Chen and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: Identifying the input-output relationship of a system or discovering the evolutionary law of a signal on the basis of observation data, and applying the constructed mathematical model to predicting, controlling or extracting other useful information constitute a problem that has been drawing a lot of attention from engineering and gaining more and more importance in econo metrics, biology, environmental science and other related areas. Over the last 30-odd years, research on this problem has rapidly developed in various areas under different terms, such as time series analysis, signal processing and system identification. Since the randomness almost always exists in real systems and in observation data, and since the random process is sometimes used to model the uncertainty in systems, it is reasonable to consider the object as a stochastic system. In some applications identification can be carried out off line, but in other cases this is impossible, for example, when the structure or the parameter of the system depends on the sample, or when the system is time-varying. In these cases we have to identify the system on line and to adjust the control in accordance with the model which is supposed to be approaching the true system during the process of identification. This is why there has been an increasing interest in identification and adaptive control for stochastic systems from both theorists and practitioners.
Book Synopsis Adaptive Approximation Based Control by : Jay A. Farrell
Download or read book Adaptive Approximation Based Control written by Jay A. Farrell and published by John Wiley & Sons. This book was released on 2006-04-14 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: A highly accessible and unified approach to the design and analysis of intelligent control systems Adaptive Approximation Based Control is a tool every control designer should have in his or her control toolbox. Mixing approximation theory, parameter estimation, and feedback control, this book presents a unified approach designed to enable readers to apply adaptive approximation based control to existing systems, and, more importantly, to gain enough intuition and understanding to manipulate and combine it with other control tools for applications that have not been encountered before. The authors provide readers with a thought-provoking framework for rigorously considering such questions as: * What properties should the function approximator have? * Are certain families of approximators superior to others? * Can the stability and the convergence of the approximator parameters be guaranteed? * Can control systems be designed to be robust in the face of noise, disturbances, and unmodeled effects? * Can this approach handle significant changes in the dynamics due to such disruptions as system failure? * What types of nonlinear dynamic systems are amenable to this approach? * What are the limitations of adaptive approximation based control? Combining theoretical formulation and design techniques with extensive use of simulation examples, this book is a stimulating text for researchers and graduate students and a valuable resource for practicing engineers.
Book Synopsis Adaptive Control Tutorial by : Petros Ioannou
Download or read book Adaptive Control Tutorial written by Petros Ioannou and published by SIAM. This book was released on 2006-01-01 with total page 401 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Optimal, Predictive, and Adaptive Control by : Edoardo Mosca
Download or read book Optimal, Predictive, and Adaptive Control written by Edoardo Mosca and published by Pearson Education. This book was released on 1995 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: Using a common unifying framework, this volume explores the main topics of Linear Quadratic control, predictive control, and adaptive predictive control -- in terms of theoretical foundations, analysis and design methodologies, and application-orient ed tools.Presents LQ and LQG control via two alternative approaches: the Dynamic Programming (DP) and the Polynomial Equation (PE) approach. Discusses predicable control, an important tool in industrial applications, within the framework of LQ control, and presents innovative predictive control schemes having guaranteed stability properties. Offers a unique, thorough presentation of indirect adaptive multi-step predictive controllers, with detailed proofs of globally convergent schemes for both the ideal and the bounded disturbance case. Extends the self-tuning property of one-step-ahead control to multi-step control.For engineers and mathematicians interested in the theory, analysis and design methodologies, and application-oriented tools of optimal, predictive and adaptive control.
Book Synopsis Adaptive Optimal Control by : Robert R. Bitmead
Download or read book Adaptive Optimal Control written by Robert R. Bitmead and published by . This book was released on 1990 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: Exploring connections between adaptive control theory and practice, this book treats the techniques of linear quadratic optimal control and estimation (Kalman filtering), recursive identification, linear systems theory and robust arguments.
Book Synopsis Lectures on Adaptive Parameter Estimation by : C. Richard Johnson
Download or read book Lectures on Adaptive Parameter Estimation written by C. Richard Johnson and published by Prentice Hall. This book was released on 1988 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis System Identification and Adaptive Control by : Yiannis Boutalis
Download or read book System Identification and Adaptive Control written by Yiannis Boutalis and published by Springer Science & Business. This book was released on 2014-04-23 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Model-Reference Adaptive Control by : Nhan T. Nguyen
Download or read book Model-Reference Adaptive Control written by Nhan T. Nguyen and published by Springer. This book was released on 2018-03-01 with total page 453 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Learning-Based Adaptive Control by : Mouhacine Benosman
Download or read book Learning-Based Adaptive Control written by Mouhacine Benosman and published by Butterworth-Heinemann. This book was released on 2016-08-02 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
