Download or read book Adaptive Identification and Control of Uncertain Systems with Non smooth Dynamics written by Jing Na and published by Academic Press. This book was released on 2018-06-12 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive Identification and Control of Uncertain Systems with Nonsmooth Dynamics reports some of the latest research on modeling, identification and adaptive control for systems with nonsmooth dynamics (e.g., backlash, dead zone, friction, saturation, etc). The authors present recent research results for the modelling and control designs of uncertain systems with nonsmooth dynamics, such as friction, dead-zone, saturation and hysteresis, etc., with particular applications in servo systems. The book is organized into 19 chapters, distributed in five parts concerning the four types of nonsmooth characteristics, namely friction, dead-zone, saturation and hysteresis, respectively. Practical experiments are also included to validate and exemplify the proposed approaches. This valuable resource can help both researchers and practitioners to learn and understand nonlinear adaptive control designs. Academics, engineers and graduate students in the fields of electrical engineering, control systems, mechanical engineering, applied mathematics and computer science can benefit from the book. It can be also used as a reference book on adaptive control for servo systems for students with some background in control engineering. - Explains the latest research outputs on modeling, identification and adaptive control for systems with nonsmooth dynamics - Provides practical application and experimental results for robotic systems, and servo motors

Download or read book Nonlinear and Adaptive Control with Applications written by Alessandro Astolfi and published by Springer Science & Business Media. This book was released on 2007-12-06 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Adaptive Nonlinear System Identification written by Tokunbo Ogunfunmi and published by Springer Science & Business Media. This book was released on 2007-09-05 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Nonlinear Identification and Control written by G.P. Liu and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this monograph is to give the broad aspects of nonlinear identification and control using neural networks. It uses a number of simulated and industrial examples throughout, to demonstrate the operation of nonlinear identification and control techniques using neural networks.

Download or read book Identification and Adaptive Control for Nonlinear Systems and Applications written by Jianhua Zhang and published by Academic Press. This book was released on 2022-03-15 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Nonlinear Identification and Adaptive Control written by Dennis S. Bernstein and published by . This book was released on 2004 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Model Free Adaptive Control written by Zhongsheng Hou and published by CRC Press. This book was released on 2013-09-24 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

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.

Download or read book Adaptive Learning Methods for Nonlinear System Modeling written by Danilo Comminiello and published by Butterworth-Heinemann. This book was released on 2018-06-11 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 introduced by the unknown system. In particular, the methods presented in this book are based on online learning approaches, which process the data example-by-example and allow to model even complex nonlinearities, e.g., showing time-varying and dynamic behaviors. Possible fields of applications of such algorithms includes distributed sensor networks, wireless communications, channel identification, predictive maintenance, wind prediction, network security, vehicular networks, active noise control, information forensics and security, tracking control in mobile robots, power systems, and nonlinear modeling in big data, among many others. This book serves as a crucial resource for researchers, PhD and post-graduate students working in the areas of machine learning, signal processing, adaptive filtering, nonlinear control, system identification, cooperative systems, computational intelligence. This book may be also of interest to the industry market and practitioners working with a wide variety of nonlinear systems. - Presents the key trends and future perspectives in the field of nonlinear signal processing and adaptive learning. - Introduces novel solutions and improvements over the state-of-the-art methods in the very exciting area of online and adaptive nonlinear identification. - Helps readers understand important methods that are effective in nonlinear system modelling, suggesting the right methodology to address particular issues.

Download or read book Fuzzy System Identification and Adaptive Control written by Ruiyun Qi and published by Springer. This book was released on 2019-06-11 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Nonlinear Identification and Adaptive Control written by and published by . This book was released on 2004 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. Adaptive stabilization algorithms are developed for uncertain linear and nonlinear systems under full-state feedback, as well as linear systems with unknown but bounded relative degree. Extensions to discrete-time systems are addressed. Adaptive command-following algorithms are developed for spacecraft and demonstrated on an experimental testbed. Adaptive disturbance rejection algorithms are developed for tonal and broadband disturbances. Nonlinear control algorithms are developed for shape change actuation for spacecraft. Semistability theory is developed to support research in adaptive control.

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.

Download or read book Nonlinear and Adaptive Control Systems written by Zhengtao Ding and published by Institution of Engineering and Technology. This book was released on 2013-04-04 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: An adaptive system for linear systems with unknown parameters is a nonlinear system. The analysis of such adaptive systems requires similar techniques to analyse nonlinear systems. Therefore it is natural to treat adaptive control as a part of nonlinear control systems. Nonlinear and Adaptive Control Systems treats nonlinear control and adaptive controlin a unified framework, presenting the major results at a moderate mathematical level, suitable for MSc students and engineers with undergraduate degrees. Topics covered include introduction to nonlinear systems; state space models; describing functions forcommon nonlinear components; stability theory; feedback linearization; adaptive control; nonlinear observer design; backstepping design; disturbance rejection and output regulation; and control applications, including harmonic estimation and rejection inpower distribution systems, observer and control design for circadian rhythms, and discrete-time implementation of continuous-timenonlinear control laws.

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

Download or read book Non Identifier Based High Gain Adaptive Control written by Achim Ilchmann and published by Springer. This book was released on 1993-08-18 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the last decade the field of adaptive control where no identification mechanisms are invoked has become a major research topic. This book presents a state-of-the-art report on the following more specific area: the system classes under consideration contain linear (possibly nonlinearly perturbed), finite dimensional, continuous time systems which are stabilizable by high-gain output feedback. The properties of minimum phase systems and strictly positive real systems are studied in their own right. These results are applied to design simple adaptive controllers involving a switching strategy which is mainly tuned by a one parameter controller based on output data alone. Control objectives are stabilization, tracking, -tracking and servomechanism action. In addition, robustness with respect to nonlinear perturbations and performance improvements are investigated.

Download or read book Adaptive Control of Parabolic PDEs written by Andrey Smyshlyaev and published by Princeton University Press. This book was released on 2010-07-01 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces a comprehensive methodology for adaptive control design of parabolic partial differential equations with unknown functional parameters, including reaction-convection-diffusion systems ubiquitous in chemical, thermal, biomedical, aerospace, and energy systems. Andrey Smyshlyaev and Miroslav Krstic develop explicit feedback laws that do not require real-time solution of Riccati or other algebraic operator-valued equations. The book emphasizes stabilization by boundary control and using boundary sensing for unstable PDE systems with an infinite relative degree. The book also presents a rich collection of methods for system identification of PDEs, methods that employ Lyapunov, passivity, observer-based, swapping-based, gradient, and least-squares tools and parameterizations, among others. Including a wealth of stimulating ideas and providing the mathematical and control-systems background needed to follow the designs and proofs, the book will be of great use to students and researchers in mathematics, engineering, and physics. It also makes a valuable supplemental text for graduate courses on distributed parameter systems and adaptive control.

Download or read book Functional Series Identification of Nonlinear Systems for Adaptive Control written by Firman Dean King and published by . This book was released on 1980 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: