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Self Learning Control Of Finite Markov Chains
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Book Synopsis Self-Learning Control of Finite Markov Chains by : A.S. Poznyak
Download or read book Self-Learning Control of Finite Markov Chains written by A.S. Poznyak and published by CRC Press. This book was released on 2018-10-03 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents a number of new and potentially useful self-learning (adaptive) control algorithms and theoretical as well as practical results for both unconstrained and constrained finite Markov chains-efficiently processing new information by adjusting the control strategies directly or indirectly.
Book Synopsis Optimization and Games for Controllable Markov Chains by : Julio B. Clempner
Download or read book Optimization and Games for Controllable Markov Chains written by Julio B. Clempner and published by Springer Nature. This book was released on 2023-12-13 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book considers a class of ergodic finite controllable Markov's chains. The main idea behind the method, described in this book, is to develop the original discrete optimization problems (or game models) in the space of randomized formulations, where the variables stand in for the distributions (mixed strategies or preferences) of the original discrete (pure) strategies in the use. The following suppositions are made: a finite state space, a limited action space, continuity of the probabilities and rewards associated with the actions, and a necessity for accessibility. These hypotheses lead to the existence of an optimal policy. The best course of action is always stationary. It is either simple (i.e., nonrandomized stationary) or composed of two nonrandomized policies, which is equivalent to randomly selecting one of two simple policies throughout each epoch by tossing a biased coin. As a bonus, the optimization procedure just has to repeatedly solve the time-average dynamic programming equation, making it theoretically feasible to choose the optimum course of action under the global restriction. In the ergodic cases the state distributions, generated by the corresponding transition equations, exponentially quickly converge to their stationary (final) values. This makes it possible to employ all widely used optimization methods (such as Gradient-like procedures, Extra-proximal method, Lagrange's multipliers, Tikhonov's regularization), including the related numerical techniques. In the book we tackle different problems and theoretical Markov models like controllable and ergodic Markov chains, multi-objective Pareto front solutions, partially observable Markov chains, continuous-time Markov chains, Nash equilibrium and Stackelberg equilibrium, Lyapunov-like function in Markov chains, Best-reply strategy, Bayesian incentive-compatible mechanisms, Bayesian Partially Observable Markov Games, bargaining solutions for Nash and Kalai-Smorodinsky formulations, multi-traffic signal-control synchronization problem, Rubinstein's non-cooperative bargaining solutions, the transfer pricing problem as bargaining.
Book Synopsis New Perspectives and Applications of Modern Control Theory by : Julio B. Clempner
Download or read book New Perspectives and Applications of Modern Control Theory written by Julio B. Clempner and published by Springer. This book was released on 2017-09-30 with total page 539 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited monograph contains research contributions on a wide range of topics such as stochastic control systems, adaptive control, sliding mode control and parameter identification methods. The book also covers applications of robust and adaptice control to chemical and biotechnological systems. This collection of papers commemorates the 70th birthday of Dr. Alexander S. Poznyak.
Book Synopsis Deterministic Learning Theory for Identification, Recognition, and Control by : Cong Wang
Download or read book Deterministic Learning Theory for Identification, Recognition, and Control written by Cong Wang and published by CRC Press. This book was released on 2018-10-03 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deterministic Learning Theory for Identification, Recognition, and Control presents a unified conceptual framework for knowledge acquisition, representation, and knowledge utilization in uncertain dynamic environments. It provides systematic design approaches for identification, recognition, and control of linear uncertain systems. Unlike many books currently available that focus on statistical principles, this book stresses learning through closed-loop neural control, effective representation and recognition of temporal patterns in a deterministic way. A Deterministic View of Learning in Dynamic Environments The authors begin with an introduction to the concepts of deterministic learning theory, followed by a discussion of the persistent excitation property of RBF networks. They describe the elements of deterministic learning, and address dynamical pattern recognition and pattern-based control processes. The results are applicable to areas such as detection and isolation of oscillation faults, ECG/EEG pattern recognition, robot learning and control, and security analysis and control of power systems. A New Model of Information Processing This book elucidates a learning theory which is developed using concepts and tools from the discipline of systems and control. Fundamental knowledge about system dynamics is obtained from dynamical processes, and is then utilized to achieve rapid recognition of dynamical patterns and pattern-based closed-loop control via the so-called internal and dynamical matching of system dynamics. This actually represents a new model of information processing, i.e. a model of dynamical parallel distributed processing (DPDP).
Book Synopsis Advanced Process Identification and Control by : Enso Ikonen
Download or read book Advanced Process Identification and Control written by Enso Ikonen and published by CRC Press. This book was released on 2001-10-02 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: A presentation of techniques in advanced process modelling, identification, prediction, and parameter estimation for the implementation and analysis of industrial systems. The authors cover applications for the identification of linear and non-linear systems, the design of generalized predictive controllers (GPCs), and the control of multivariable systems.
Book Synopsis Simulation-Based Algorithms for Markov Decision Processes by : Hyeong Soo Chang
Download or read book Simulation-Based Algorithms for Markov Decision Processes written by Hyeong Soo Chang and published by Springer Science & Business Media. This book was released on 2013-02-26 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: Markov decision process (MDP) models are widely used for modeling sequential decision-making problems that arise in engineering, economics, computer science, and the social sciences. Many real-world problems modeled by MDPs have huge state and/or action spaces, giving an opening to the curse of dimensionality and so making practical solution of the resulting models intractable. In other cases, the system of interest is too complex to allow explicit specification of some of the MDP model parameters, but simulation samples are readily available (e.g., for random transitions and costs). For these settings, various sampling and population-based algorithms have been developed to overcome the difficulties of computing an optimal solution in terms of a policy and/or value function. Specific approaches include adaptive sampling, evolutionary policy iteration, evolutionary random policy search, and model reference adaptive search. This substantially enlarged new edition reflects the latest developments in novel algorithms and their underpinning theories, and presents an updated account of the topics that have emerged since the publication of the first edition. Includes: innovative material on MDPs, both in constrained settings and with uncertain transition properties; game-theoretic method for solving MDPs; theories for developing roll-out based algorithms; and details of approximation stochastic annealing, a population-based on-line simulation-based algorithm. The self-contained approach of this book will appeal not only to researchers in MDPs, stochastic modeling, and control, and simulation but will be a valuable source of tuition and reference for students of control and operations research.
Book Synopsis Stochastic Processes by : Kaddour Najim
Download or read book Stochastic Processes written by Kaddour Najim and published by Elsevier. This book was released on 2004-07-01 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: A 'stochastic' process is a 'random' or 'conjectural' process, and this book is concerned with applied probability and statistics. Whilst maintaining the mathematical rigour this subject requires, it addresses topics of interest to engineers, such as problems in modelling, control, reliability maintenance, data analysis and engineering involvement with insurance.This book deals with the tools and techniques used in the stochastic process – estimation, optimisation and recursive logarithms – in a form accessible to engineers and which can also be applied to Matlab. Amongst the themes covered in the chapters are mathematical expectation arising from increasing information patterns, the estimation of probability distribution, the treatment of distribution of real random phenomena (in engineering, economics, biology and medicine etc), and expectation maximisation. The latter part of the book considers optimization algorithms, which can be used, for example, to help in the better utilization of resources, and stochastic approximation algorithms, which can provide prototype models in many practical applications.*An engineering approach to applied probabilities and statistics *Presents examples related to practical engineering applications, such as reliability, randomness and use of resources*Readers with varying interests and mathematical backgrounds will find this book accessible
Book Synopsis Autonomous Mobile Robots by : Frank L. Lewis
Download or read book Autonomous Mobile Robots written by Frank L. Lewis and published by CRC Press. This book was released on 2018-10-03 with total page 511 pages. Available in PDF, EPUB and Kindle. Book excerpt: It has long been the goal of engineers to develop tools that enhance our ability to do work, increase our quality of life, or perform tasks that are either beyond our ability, too hazardous, or too tedious to be left to human efforts. Autonomous mobile robots are the culmination of decades of research and development, and their potential is seemingly unlimited. Roadmap to the Future Serving as the first comprehensive reference on this interdisciplinary technology, Autonomous Mobile Robots: Sensing, Control, Decision Making, and Applications authoritatively addresses the theoretical, technical, and practical aspects of the field. The book examines in detail the key components that form an autonomous mobile robot, from sensors and sensor fusion to modeling and control, map building and path planning, and decision making and autonomy, and to the final integration of these components for diversified applications. Trusted Guidance A duo of accomplished experts leads a team of renowned international researchers and professionals who provide detailed technical reviews and the latest solutions to a variety of important problems. They share hard-won insight into the practical implementation and integration issues involved in developing autonomous and open robotic systems, along with in-depth examples, current and future applications, and extensive illustrations. For anyone involved in researching, designing, or deploying autonomous robotic systems, Autonomous Mobile Robots is the perfect resource.
Book Synopsis Applications of Mathematics and Informatics in Military Science by : Nicholas Daras
Download or read book Applications of Mathematics and Informatics in Military Science written by Nicholas Daras and published by Springer Science & Business Media. This book was released on 2012-08-18 with total page 247 pages. Available in PDF, EPUB and Kindle. Book excerpt: Analysis, assessment, and data management are core tools required for operation research analysts. The April 2011 conference held at the Helenic Military Academy addressed these issues with efforts to collect valuable recommendations for improving analysts’ capabilities to assess and communicate the necessary qualitative data to military leaders. This unique volume is an outgrowth of the April conference and comprises of contributions from the fields of science, mathematics, and the military, bringing Greek research findings to the world. Topics cover a wide variety of mathematical methods used with application to defense and security. Each contribution considers directions and pursuits of scientists that pertain to the military as well as the theoretical background required for methods, algorithms, and techniques used in military applications. The direction of theoretical results in these applications is conveyed and open problems and future areas of focus are highlighted. A foreword will be composed by a member of N.A.T.O. or a ranking member of the armed forces. Topics covered include: applied OR and military applications, signal processing, scattering, scientific computing and applications, combat simulation and statistical modeling, satellite remote sensing, and applied informatics – cryptography and coding. The contents of this volume will be of interest to a diverse audience including military operations research analysts, the military community at large, and practitioners working with mathematical methods and applications to informatics and military science.
Book Synopsis Advanced Mathematical Tools for Automatic Control Engineers: Volume 2 by : Alexander S. Poznyak
Download or read book Advanced Mathematical Tools for Automatic Control Engineers: Volume 2 written by Alexander S. Poznyak and published by Elsevier. This book was released on 2009-08-13 with total page 568 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advanced Mathematical Tools for Automatic Control Engineers, Volume 2: Stochastic Techniques provides comprehensive discussions on statistical tools for control engineers. The book is divided into four main parts. Part I discusses the fundamentals of probability theory, covering probability spaces, random variables, mathematical expectation, inequalities, and characteristic functions. Part II addresses discrete time processes, including the concepts of random sequences, martingales, and limit theorems. Part III covers continuous time stochastic processes, namely Markov processes, stochastic integrals, and stochastic differential equations. Part IV presents applications of stochastic techniques for dynamic models and filtering, prediction, and smoothing problems. It also discusses the stochastic approximation method and the robust stochastic maximum principle. - Provides comprehensive theory of matrices, real, complex and functional analysis - Provides practical examples of modern optimization methods that can be effectively used in variety of real-world applications - Contains worked proofs of all theorems and propositions presented
Download or read book Optimal Control written by Zoran Gajic and published by CRC Press. This book was released on 2018-10-03 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unique in scope, Optimal Control: Weakly Coupled Systems and Applications provides complete coverage of modern linear, bilinear, and nonlinear optimal control algorithms for both continuous-time and discrete-time weakly coupled systems, using deterministic as well as stochastic formulations. This book presents numerous applications to real world systems from various industries, including aerospace, and discusses the design of subsystem-level optimal filters. Organized into independent chapters for easy access to the material, this text also contains several case studies, examples, exercises, computer assignments, and formulations of research problems to help instructors and students.
Book Synopsis Linear Control Theory by : Shankar P. Bhattacharyya
Download or read book Linear Control Theory written by Shankar P. Bhattacharyya and published by CRC Press. This book was released on 2018-10-03 with total page 679 pages. Available in PDF, EPUB and Kindle. Book excerpt: Successfully classroom-tested at the graduate level, Linear Control Theory: Structure, Robustness, and Optimization covers three major areas of control engineering (PID control, robust control, and optimal control). It provides balanced coverage of elegant mathematical theory and useful engineering-oriented results. The first part of the book develops results relating to the design of PID and first-order controllers for continuous and discrete-time linear systems with possible delays. The second section deals with the robust stability and performance of systems under parametric and unstructured uncertainty. This section describes several elegant and sharp results, such as Kharitonov’s theorem and its extensions, the edge theorem, and the mapping theorem. Focusing on the optimal control of linear systems, the third part discusses the standard theories of the linear quadratic regulator, Hinfinity and l1 optimal control, and associated results. Written by recognized leaders in the field, this book explains how control theory can be applied to the design of real-world systems. It shows that the techniques of three term controllers, along with the results on robust and optimal control, are invaluable to developing and solving research problems in many areas of engineering.
Book Synopsis Fundamentals in Modeling and Control of Mobile Manipulators by : Zhijun Li
Download or read book Fundamentals in Modeling and Control of Mobile Manipulators written by Zhijun Li and published by CRC Press. This book was released on 2016-04-19 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mobile manipulators combine the advantages of mobile platforms and robotic arms, extending their operational range and functionality to large spaces and remote, demanding, and/or dangerous environments. They also bring complexity and difficulty in dynamic modeling and control system design.
Book Synopsis Tensor Product Model Transformation in Polytopic Model-Based Control by : Péter Baranyi
Download or read book Tensor Product Model Transformation in Polytopic Model-Based Control written by Péter Baranyi and published by CRC Press. This book was released on 2018-09-03 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: Tensor Product Model Transformation in Polytopic Model-Based Control offers a new perspective of control system design. Instead of relying solely on the formulation of more effective LMIs, which is the widely adopted approach in existing LMI-related studies, this cutting-edge book calls for a systematic modification and reshaping of the polytopic convex hull to achieve enhanced performance. Varying the convexity of the resulting TP canonical form is a key new feature of the approach. The book concentrates on reducing analytical derivations in the design process, echoing the recent paradigm shift on the acceptance of numerical solution as a valid form of output to control system problems. The salient features of the book include: Presents a new HOSVD-based canonical representation for (qLPV) models that enables trade-offs between approximation accuracy and computation complexity Supports a conceptually new control design methodology by proposing TP model transformation that offers a straightforward way of manipulating different types of convexity to appear in polytopic representation Introduces a numerical transformation that has the advantage of readily accommodating models described by non-conventional modeling and identification approaches, such as neural networks and fuzzy rules Presents a number of practical examples to demonstrate the application of the approach to generate control system design for complex (qLPV) systems and multiple control objectives. The authors’ approach is based on an extended version of singular value decomposition applicable to hyperdimensional tensors. Under the approach, trade-offs between approximation accuracy and computation complexity can be performed through the singular values to be retained in the process. The use of LMIs enables the incorporation of multiple performance objectives into the control design problem and assurance of a solution via convex optimization if feasible. Tensor Product Model Transformation in Polytopic Model-Based Control includes examples and incorporates MATLAB® Toolbox TPtool. It provides a reference guide for graduate students, researchers, engineers, and practitioners who are dealing with nonlinear systems control applications.
Book Synopsis Optimal and Robust Scheduling for Networked Control Systems by : Stefano Longo
Download or read book Optimal and Robust Scheduling for Networked Control Systems written by Stefano Longo and published by CRC Press. This book was released on 2018-09-03 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimal and Robust Scheduling for Networked Control Systems tackles the problem of integrating system components—controllers, sensors, and actuators—in a networked control system. It is common practice in industry to solve such problems heuristically, because the few theoretical results available are not comprehensive and cannot be readily applied by practitioners. This book offers a solution to the deterministic scheduling problem that is based on rigorous control theoretical tools but also addresses practical implementation issues. Helping to bridge the gap between control theory and computer science, it suggests that the consideration of communication constraints at the design stage will significantly improve the performance of the control system. Technical Results, Design Techniques, and Practical Applications The book brings together well-known measures for robust performance as well as fast stochastic algorithms to assist designers in selecting the best network configuration and guaranteeing the speed of offline optimization. The authors propose a unifying framework for modelling NCSs with time-triggered communication and present technical results. They also introduce design techniques, including for the codesign of a controller and communication sequence and for the robust design of a communication sequence for a given controller. Case studies explore the use of the FlexRay TDMA and time-triggered control area network (CAN) protocols in an automotive control system. Practical Solutions to Your Time-Triggered Communication Problems This unique book develops ready-to-use engineering tools for large-scale control system integration with a focus on robustness and performance. It emphasizes techniques that are directly applicable to time-triggered communication problems in the automotive industry and in avionics, robotics, and automated manufacturing.
Book Synopsis Discrete-Time Recurrent Neural Control by : Edgar N. Sanchez
Download or read book Discrete-Time Recurrent Neural Control written by Edgar N. Sanchez and published by CRC Press. This book was released on 2018-09-03 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents recent advances in the theory of neural control for discrete-time nonlinear systems with multiple inputs and multiple outputs. The simulation results that appear in each chapter include rigorous mathematical analyses, based on the Lyapunov approach, to establish its properties. The book contains two sections: the first focuses on the analyses of control techniques; the second is dedicated to illustrating results of real-time applications. It also provides solutions for the output trajectory tracking problem of unknown nonlinear systems based on sliding modes and inverse optimal control scheme. "This book on Discrete-time Recurrent Neural Control is unique in the literature, with new knowledge and information about the new technique of recurrent neural control especially for discrete-time systems. The book is well organized and clearly presented. It will be welcome by a wide range of researchers in science and engineering, especially graduate students and junior researchers who want to learn the new notion of recurrent neural control. I believe it will have a good market. It is an excellent book after all." — Guanrong Chen, City University of Hong Kong "This book includes very relevant topics, about neural control. In these days, Artificial Neural Networks have been recovering their relevance and well-stablished importance, this due to its great capacity to process big amounts of data. Artificial Neural Networks development always is related to technological advancements; therefore, it is not a surprise that now we are being witnesses of this new era in Artificial Neural Networks, however most of the developments in this research area only focuses on applicability of the proposed schemes. However, Edgar N. Sanchez author of this book does not lose focus and include both important applications as well as a deep theoretical analysis of Artificial Neural Networks to control discrete-time nonlinear systems. It is important to remark that first, the considered Artificial Neural Networks are development in discrete-time this simplify its implementation in real-time; secondly, the proposed applications ranging from modelling of unknown discrete-time on linear systems to control electrical machines with an emphasize to renewable energy systems. However, its applications are not limited to these kind of systems, due to their theoretical foundation it can be applicable to a large class of nonlinear systems. All of these is supported by the solid research done by the author." — Alma Y. Alanis, University of Guadalajara, Mexico "This book discusses in detail; how neural networks can be used for optimal as well as robust control design. Design of neural network controllers for real time applications such as induction motors, boost converters, inverted pendulum and doubly fed induction generators has also been carried out which gives the book an edge over other similar titles. This book will be an asset for the novice to the experienced ones." — Rajesh Joseph Abraham, Indian Institute of Space Science & Technology, Thiruvananthapuram, India
Book Synopsis Chaos in Automatic Control by : Wilfrid Perruquetti
Download or read book Chaos in Automatic Control written by Wilfrid Perruquetti and published by CRC Press. This book was released on 2018-10-03 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: Chaotic behavior arises in a variety of control settings. In some cases, it is beneficial to remove this behavior; in others, introducing or taking advantage of the existing chaotic components can be useful for example in cryptography. Chaos in Automatic Control surveys the latest methods for inserting, taking advantage of, or removing chaos in a variety of applications. This book supplies the theoretical and pedagogical basis of chaos in control systems along with new concepts and recent developments in the field. Presented in three parts, the book examines open-loop analysis, closed-loop control, and applications of chaos in control systems. The first section builds a background in the mathematics of ordinary differential and difference equations on which the remainder of the book is based. It includes an introductory chapter by Christian Mira, a pioneer in chaos research. The next section explores solutions to problems arising in observation and control of closed-loop chaotic control systems. These include model-independent control methods, strategies such as H-infinity and sliding modes, polytopic observers, normal forms using homogeneous transformations, and observability normal forms. The final section explores applications in wireless transmission, optics, power electronics, and cryptography. Chaos in Automatic Control distills the latest thinking in chaos while relating it to the most recent developments and applications in control. It serves as a platform for developing more robust, autonomous, intelligent, and adaptive systems.