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A General Methodology For The Adaptive Control Of Uncertain Dynamical Systems Using Multiple Models And Model Weighting
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Book Synopsis A General Methodology for the Adaptive Control of Uncertain Dynamical Systems Using Multiple Models and Model Weighting by : Ajay Rajagopal
Download or read book A General Methodology for the Adaptive Control of Uncertain Dynamical Systems Using Multiple Models and Model Weighting written by Ajay Rajagopal and published by . This book was released on 1996 with total page 60 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Proceedings of 2017 Chinese Intelligent Systems Conference by : Yingmin Jia
Download or read book Proceedings of 2017 Chinese Intelligent Systems Conference written by Yingmin Jia and published by Springer. This book was released on 2017-09-27 with total page 762 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents selected research papers from CISC’17, held in MudanJiang, China. The topics covered include Multi-agent system, Evolutionary Computation, Artificial Intelligence, Complex systems, Computation intelligence and soft computing, Intelligent control, Advanced control technology, Robotics and applications, Intelligent information processing, Iterative learning control, Machine Learning, and etc. Engineers and researchers from academia, industry, and government can gain valuable insights into solutions combining ideas from multiple disciplines in the field of intelligent systems.
Book Synopsis Adaptive Control of Dynamic Systems with Uncertainty and Quantization by : Jing Zhou
Download or read book Adaptive Control of Dynamic Systems with Uncertainty and Quantization written by Jing Zhou and published by CRC Press. This book was released on 2021-12-14 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a series of innovative technologies and research results on adaptive control of dynamic systems with quantization, uncertainty, and nonlinearity, including the theoretical success and practical development such as the approaches for stability analysis, the compensation of quantization, the treatment of subsystem interactions, and the improvement of system tracking and transient performance. Novel solutions by adopting backstepping design tools to a number of hotspots and challenging problems in the area of adaptive control are provided. In the first three chapters, the general design procedures and stability analysis of backstepping controllers and the basic descriptions and properties of quantizers are introduced as preliminary knowledge for this book. In the remainder of this book, adaptive control schemes are introduced to compensate for the effects of input quantization, state quantization, both input and state/output quantization for uncertain nonlinear systems and are applied to helicopter systems and DC Microgrid. Discussion remarks are provided in each chapter highlighting new approaches and contributions to emphasize the novelty of the presented design and analysis methods. Simulation results are also given in each chapter to show the effectiveness of these methods. This book is helpful to learn and understand the fundamental backstepping schemes for state feedback control and output feedback control. It can be used as a reference book or a textbook on adaptive quantized control for students with some background in feedback control systems. Researchers, graduate students, and engineers in the fields of control, information, and communication, electrical engineering, mechanical engineering, computer science, and others will benefit from this book.
Book Synopsis Proceedings of the ASME Dynamic Systems and Control Division by :
Download or read book Proceedings of the ASME Dynamic Systems and Control Division written by and published by . This book was released on 1996 with total page 966 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Robust Control of Uncertain Dynamic Systems by : Rama K. Yedavalli
Download or read book Robust Control of Uncertain Dynamic Systems written by Rama K. Yedavalli and published by Springer Science & Business Media. This book was released on 2013-12-05 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook aims to provide a clear understanding of the various tools of analysis and design for robust stability and performance of uncertain dynamic systems. In model-based control design and analysis, mathematical models can never completely represent the “real world” system that is being modeled, and thus it is imperative to incorporate and accommodate a level of uncertainty into the models. This book directly addresses these issues from a deterministic uncertainty viewpoint and focuses on the interval parameter characterization of uncertain systems. Various tools of analysis and design are presented in a consolidated manner. This volume fills a current gap in published works by explicitly addressing the subject of control of dynamic systems from linear state space framework, namely using a time-domain, matrix-theory based approach. This book also: Presents and formulates the robustness problem in a linear state space model framework. Illustrates various systems level methodologies with examples and applications drawn from aerospace, electrical and mechanical engineering. Provides connections between lyapunov-based matrix approach and the transfer function based polynomial approaches. Robust Control of Uncertain Dynamic Systems: A Linear State Space Approach is an ideal book for first year graduate students taking a course in robust control in aerospace, mechanical, or electrical engineering.
Book Synopsis Multi-Resolution Methods for Modeling and Control of Dynamical Systems by : Puneet Singla
Download or read book Multi-Resolution Methods for Modeling and Control of Dynamical Systems written by Puneet Singla and published by CRC Press. This book was released on 2008-08-01 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unifying the most important methodology in this field, Multi-Resolution Methods for Modeling and Control of Dynamical Systems explores existing approximation methods as well as develops new ones for the approximate solution of large-scale dynamical system problems. It brings together a wide set of material from classical orthogonal function
Book Synopsis Experimental Results of a Model Reference Adaptive Control Approach on an Interconnected Uncertain Dynamical System by : Kemberly Ann Cespedes
Download or read book Experimental Results of a Model Reference Adaptive Control Approach on an Interconnected Uncertain Dynamical System written by Kemberly Ann Cespedes and published by . This book was released on 2019 with total page 21 pages. Available in PDF, EPUB and Kindle. Book excerpt: The objective of this thesis is to show the experimental validation of recently proposed adaptive control architecture for uncertain dynamical systems. The experimental validation is conducted on a benchmark mechanical system setup composed of two carts, one actuated and one unactuated, physically interconnected through a spring. Specifically, an approach has been recently proposed to stabilize an overall interconnected system in the presence of unknown physical interconnections as well as system uncertainties in the context of model reference adaptive control. This uncertain dynamical system consists of actuated and unactuated portions physically interconnected to each other. In addition, the previous work enforces performance guarantees individually on both the actuated and unactuated portions of the interconnected system. In particular, a set-theoretic model reference adaptive control approach has been used in conjunction with linear matrix inequalities to enforce these performance guarantees that is restricting the respective system error trajectories of the actuated and unactuated dynamics inside a-priori, user defined compact sets. As stated above, the overarching contribution of this thesis is to present experimental results for the purpose of demonstrating the efficacy of the previously proposed approach on a benchmark mechanical system setup involving an actuated cart coupled with an unactuated cart through a spring in the presence of both unknown friction and unknown uncertainties. It is experimentally observed that utilizing the proposed approach stabilizes and restricts the respective system error trajectories of the interconnected system.
Book Synopsis A New Approach to Multi-Model Adaptive Control by : Mohamad Shahab
Download or read book A New Approach to Multi-Model Adaptive Control written by Mohamad Shahab and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive control is an approach used to deal with systems with uncertain or time-varying parameters. A classical adaptive controller typically consists of a linear time-invariant (LTI) control law together with a tuning mechanism which adjusts its parameters. Usually, though not exclusively, discrete-time adaptive controllers provide only asymptotic stability and possibly bounded-noise bounded-state stability; neither exponential stability nor a bounded noise gain is typically proven. Recently it has been shown that if we employ a parameter estimator based on the original Projection Algorithm together with projecting the parameter estimates onto a given compact and convex set, then the adaptive controller guarantees linear-like closed-loop behavior: exponential stability, a bounded noise gain and a convolution bound on the exogenous inputs. In this thesis, the overarching objective is to show that we can prove these same desirable linear-like properties in a wide range of adaptive control problems without the convexity assumption: the main idea is to use multiple estimators and a switching algorithm. Indeed, we show that those properties arise in a surprisingly natural way. We first prove a general result that exponential stability and a convolution bound on the closed-loop behavior can be leveraged to show tolerance to a degree of time-variations and unmodelled dynamics, i.e. such closed-loop properties guarantee robustness. After reviewing the original Projection Algorithm and introducing the reader to our slightly revised version, we turn our attention to controller design, with a focus on a non-convex set of plant uncertainty. As a starting point, we first consider first-order plants incorporating a simple switching algorithm. We then extend the approach to a class of nonlinear plants (which have stable zero dynamics); we consider both cases of convex and non-convex sets of parameter uncertainty. Afterwards, we turn to possibly non-minimum phase LTI plants; first we consider the stabilization problem for which we have two convex sets of uncertainty; then, we turn to the problem of tracking the sum of a finite number of sinusoids of known frequencies subject to an unknown plant order and a general compact set of uncertainty.
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 International Aerospace Abstracts by :
Download or read book International Aerospace Abstracts written by and published by . This book was released on 1999 with total page 1020 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Applied mechanics reviews written by and published by . This book was released on 1948 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Artificial Neural Networks for Engineering Applications by : Alma Y. Alanis
Download or read book Artificial Neural Networks for Engineering Applications written by Alma Y. Alanis and published by Academic Press. This book was released on 2019-02-07 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Neural Networks for Engineering Applications presents current trends for the solution of complex engineering problems that cannot be solved through conventional methods. The proposed methodologies can be applied to modeling, pattern recognition, classification, forecasting, estimation, and more. Readers will find different methodologies to solve various problems, including complex nonlinear systems, cellular computational networks, waste water treatment, attack detection on cyber-physical systems, control of UAVs, biomechanical and biomedical systems, time series forecasting, biofuels, and more. Besides the real-time implementations, the book contains all the theory required to use the proposed methodologies for different applications. Presents the current trends for the solution of complex engineering problems that cannot be solved through conventional methods Includes real-life scenarios where a wide range of artificial neural network architectures can be used to solve the problems encountered in engineering Contains all the theory required to use the proposed methodologies for different applications
Book Synopsis Modelling and Control of Dynamic Systems Using Gaussian Process Models by : Juš Kocijan
Download or read book Modelling and Control of Dynamic Systems Using Gaussian Process Models written by Juš Kocijan and published by Springer. This book was released on 2015-11-21 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph opens up new horizons for engineers and researchers in academia and in industry dealing with or interested in new developments in the field of system identification and control. It emphasizes guidelines for working solutions and practical advice for their implementation rather than the theoretical background of Gaussian process (GP) models. The book demonstrates the potential of this recent development in probabilistic machine-learning methods and gives the reader an intuitive understanding of the topic. The current state of the art is treated along with possible future directions for research. Systems control design relies on mathematical models and these may be developed from measurement data. This process of system identification, when based on GP models, can play an integral part of control design in data-based control and its description as such is an essential aspect of the text. The background of GP regression is introduced first with system identification and incorporation of prior knowledge then leading into full-blown control. The book is illustrated by extensive use of examples, line drawings, and graphical presentation of computer-simulation results and plant measurements. The research results presented are applied in real-life case studies drawn from successful applications including: a gas–liquid separator control; urban-traffic signal modelling and reconstruction; and prediction of atmospheric ozone concentration. A MATLAB® toolbox, for identification and simulation of dynamic GP models is provided for download.
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.
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 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents the design, analysis, and application of a wide variety of algorithms that can be used to manage dynamical systems with unknown parameters.
Book Synopsis Robust Adaptive Dynamic Programming by : Yu Jiang
Download or read book Robust Adaptive Dynamic Programming written by Yu Jiang and published by John Wiley & Sons. This book was released on 2017-05-08 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive look at state-of-the-art ADP theory and real-world applications This book fills a gap in the literature by providing a theoretical framework for integrating techniques from adaptive dynamic programming (ADP) and modern nonlinear control to address data-driven optimal control design challenges arising from both parametric and dynamic uncertainties. Traditional model-based approaches leave much to be desired when addressing the challenges posed by the ever-increasing complexity of real-world engineering systems. An alternative which has received much interest in recent years are biologically-inspired approaches, primarily RADP. Despite their growing popularity worldwide, until now books on ADP have focused nearly exclusively on analysis and design, with scant consideration given to how it can be applied to address robustness issues, a new challenge arising from dynamic uncertainties encountered in common engineering problems. Robust Adaptive Dynamic Programming zeros in on the practical concerns of engineers. The authors develop RADP theory from linear systems to partially-linear, large-scale, and completely nonlinear systems. They provide in-depth coverage of state-of-the-art applications in power systems, supplemented with numerous real-world examples implemented in MATLAB. They also explore fascinating reverse engineering topics, such how ADP theory can be applied to the study of the human brain and cognition. In addition, the book: Covers the latest developments in RADP theory and applications for solving a range of systems’ complexity problems Explores multiple real-world implementations in power systems with illustrative examples backed up by reusable MATLAB code and Simulink block sets Provides an overview of nonlinear control, machine learning, and dynamic control Features discussions of novel applications for RADP theory, including an entire chapter on how it can be used as a computational mechanism of human movement control Robust Adaptive Dynamic Programming is both a valuable working resource and an intriguing exploration of contemporary ADP theory and applications for practicing engineers and advanced students in systems theory, control engineering, computer science, and applied mathematics.
Book Synopsis Scientific and Technical Aerospace Reports by :
Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1995 with total page 994 pages. Available in PDF, EPUB and Kindle. Book excerpt:
