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Book Uncertain Optimal Control

Download or read book Uncertain Optimal Control written by Yuanguo Zhu and published by Springer. This book was released on 2018-08-29 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces the theory and applications of uncertain optimal control, and establishes two types of models including expected value uncertain optimal control and optimistic value uncertain optimal control. These models, which have continuous-time forms and discrete-time forms, make use of dynamic programming. The uncertain optimal control theory relates to equations of optimality, uncertain bang-bang optimal control, optimal control with switched uncertain system, and optimal control for uncertain system with time-delay. Uncertain optimal control has applications in portfolio selection, engineering, and games. The book is a useful resource for researchers, engineers, and students in the fields of mathematics, cybernetics, operations research, industrial engineering, artificial intelligence, economics, and management science.

Book Optimal Control  Expectations and Uncertainty

Download or read book Optimal Control Expectations and Uncertainty written by Sean Holly and published by Cambridge University Press. This book was released on 1989-07-20 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: An examination of how the rational expectations revolution and game theory have enhanced the understanding of how an economy functions.

Book Uncertain Models and Robust Control

Download or read book Uncertain Models and Robust Control written by Alexander Weinmann and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 699 pages. Available in PDF, EPUB and Kindle. Book excerpt: This coherent introduction to the theory and methods of robust control system design clarifies and unifies the presentation of significant derivations and proofs. The book contains a thorough treatment of important material of uncertainties and robust control otherwise scattered throughout the literature.

Book Optimization and Control for Partial Differential Equations

Download or read book Optimization and Control for Partial Differential Equations written by Roland Herzog and published by Walter de Gruyter GmbH & Co KG. This book was released on 2022-03-07 with total page 474 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights new developments in the wide and growing field of partial differential equations (PDE)-constrained optimization. Optimization problems where the dynamics evolve according to a system of PDEs arise in science, engineering, and economic applications and they can take the form of inverse problems, optimal control problems or optimal design problems. This book covers new theoretical, computational as well as implementation aspects for PDE-constrained optimization problems under uncertainty, in shape optimization, and in feedback control, and it illustrates the new developments on representative problems from a variety of applications.

Book Optimal Control of PDEs under Uncertainty

Download or read book Optimal Control of PDEs under Uncertainty written by Jesús Martínez-Frutos and published by Springer. This book was released on 2018-08-30 with total page 123 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a direct and comprehensive introduction to theoretical and numerical concepts in the emerging field of optimal control of partial differential equations (PDEs) under uncertainty. The main objective of the book is to offer graduate students and researchers a smooth transition from optimal control of deterministic PDEs to optimal control of random PDEs. Coverage includes uncertainty modelling in control problems, variational formulation of PDEs with random inputs, robust and risk-averse formulations of optimal control problems, existence theory and numerical resolution methods. The exposition focusses on the entire path, starting from uncertainty modelling and ending in the practical implementation of numerical schemes for the numerical approximation of the considered problems. To this end, a selected number of illustrative examples are analysed in detail throughout the book. Computer codes, written in MatLab, are provided for all these examples. This book is adressed to graduate students and researches in Engineering, Physics and Mathematics who are interested in optimal control and optimal design for random partial differential equations.

Book Constrained Control of Uncertain  Time Varying  Discrete Time Systems

Download or read book Constrained Control of Uncertain Time Varying Discrete Time Systems written by Hoai-Nam Nguyen and published by Springer. This book was released on 2014-01-02 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive development of interpolating control, this monograph demonstrates the reduced computational complexity of a ground-breaking technique compared with the established model predictive control. The text deals with the regulation problem for linear, time-invariant, discrete-time uncertain dynamical systems having polyhedral state and control constraints, with and without disturbances, and under state or output feedback. For output feedback a non-minimal state-space representation is used with old inputs and outputs as state variables. Constrained Control of Uncertain, Time-Varying, Discrete-time Systems details interpolating control in both its implicit and explicit forms. In the former at most two linear-programming or one quadratic-programming problem are solved on-line at each sampling instant to yield the value of the control variable. In the latter the control law is shown to be piecewise affine in the state, and so the state space is partitioned into polyhedral cells so that at each sampling interval the cell to which the measured state belongs must be determined. Interpolation is performed between vertex control, and a user-chosen control law in its maximal admissible set surrounding the origin. Novel proofs of recursive feasibility and asymptotic stability of the vertex control law, and of the interpolating control law are given. Algorithms for implicit and explicit interpolating control are presented in such a way that the reader may easily realize them. Each chapter includes illustrative examples, and comparisons with model predictive control in which the disparity in computational complexity is shown to be particularly in favour of interpolating control for high-order systems, and systems with uncertainty. Furthermore, the performance of the two methods proves similar except in those cases when a solution cannot be found with model predictive control at all. The book concludes with two high dimensional examples and a benchmark robust model predictive control problem: the non-isothermal continuously-stirred-tank reactor. For academic control researchers and students or for control engineers interested in implementing constrained control systems Constrained Control of Uncertain, Time-Varying, Discrete-time Systems will provide an attractive low-complexity control alternative for cases in which model predictive control is currently attempted.

Book Randomized Algorithms for Analysis and Control of Uncertain Systems

Download or read book Randomized Algorithms for Analysis and Control of Uncertain Systems written by Roberto Tempo and published by Springer Science & Business Media. This book was released on 2012-10-21 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: The presence of uncertainty in a system description has always been a critical issue in control. The main objective of Randomized Algorithms for Analysis and Control of Uncertain Systems, with Applications (Second Edition) is to introduce the reader to the fundamentals of probabilistic methods in the analysis and design of systems subject to deterministic and stochastic uncertainty. The approach propounded by this text guarantees a reduction in the computational complexity of classical control algorithms and in the conservativeness of standard robust control techniques. The second edition has been thoroughly updated to reflect recent research and new applications with chapters on statistical learning theory, sequential methods for control and the scenario approach being completely rewritten. Features: · self-contained treatment explaining Monte Carlo and Las Vegas randomized algorithms from their genesis in the principles of probability theory to their use for system analysis; · development of a novel paradigm for (convex and nonconvex) controller synthesis in the presence of uncertainty and in the context of randomized algorithms; · comprehensive treatment of multivariate sample generation techniques, including consideration of the difficulties involved in obtaining identically and independently distributed samples; · applications of randomized algorithms in various endeavours, such as PageRank computation for the Google Web search engine, unmanned aerial vehicle design (both new in the second edition), congestion control of high-speed communications networks and stability of quantized sampled-data systems. Randomized Algorithms for Analysis and Control of Uncertain Systems (second edition) is certain to interest academic researchers and graduate control students working in probabilistic, robust or optimal control methods and control engineers dealing with system uncertainties. The present book is a very timely contribution to the literature. I have no hesitation in asserting that it will remain a widely cited reference work for many years. M. Vidyasagar

Book Optimal Control of Systems with Uncertainty

Download or read book Optimal Control of Systems with Uncertainty written by W. E. Schmitendorf and published by . This book was released on 1978 with total page 83 pages. Available in PDF, EPUB and Kindle. Book excerpt: The research being performed under AFOSR Grant 76-2923 is concerned with optimally controlling a system to a specified target when disturbances or uncertainties enter the system. Two general problems in this area are being investigated. One problem is that of determining if there exists a control that assures that the system reaches a specified target set for all possible disturbances. If such a control exists, then the next problem is to determine a control which guarantees that the target is reached and it also optimal in the sense of minimizing a specified measure of the system's performance. Our research effort has been directed toward obtaining methods for answering the questions raised by these problems and thereby aiding in the design of controllers for uncertain systems. (Author).

Book Algorithmic Foundations of Robotics XII

Download or read book Algorithmic Foundations of Robotics XII written by Ken Goldberg and published by Springer. This book was released on 2021-05-21 with total page 931 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the outcomes of the 12th International Workshop on the Algorithmic Foundations of Robotics (WAFR 2016). WAFR is a prestigious, single-track, biennial international meeting devoted to recent advances in algorithmic problems in robotics. Robot algorithms are an important building block of robotic systems and are used to process inputs from users and sensors, perceive and build models of the environment, plan low-level motions and high-level tasks, control robotic actuators, and coordinate actions across multiple systems. However, developing and analyzing these algorithms raises complex challenges, both theoretical and practical. Advances in the algorithmic foundations of robotics have applications to manufacturing, medicine, distributed robotics, human–robot interaction, intelligent prosthetics, computer animation, computational biology, and many other areas. The 2016 edition of WAFR went back to its roots and was held in San Francisco, California – the city where the very first WAFR was held in 1994. Organized by Pieter Abbeel, Kostas Bekris, Ken Goldberg, and Lauren Miller, WAFR 2016 featured keynote talks by John Canny on “A Guided Tour of Computer Vision, Robotics, Algebra, and HCI,” Erik Demaine on “Replicators, Transformers, and Robot Swarms: Science Fiction through Geometric Algorithms,” Dan Halperin on “From Piano Movers to Piano Printers: Computing and Using Minkowski Sums,” and by Lydia Kavraki on “20 Years of Sampling Robot Motion.” Furthermore, it included an Open Problems Session organized by Ron Alterovitz, Florian Pokorny, and Jur van den Berg. There were 58 paper presentations during the three-day event. The organizers would like to thank the authors for their work and contributions, the reviewers for ensuring the high quality of the meeting, the WAFR Steering Committee led by Nancy Amato as well as WAFR’s fiscal sponsor, the International Federation of Robotics Research (IFRR), led by Oussama Khatib and Henrik Christensen. WAFR 2016 was an enjoyable and memorable event.

Book Modern Optimal Control

Download or read book Modern Optimal Control written by E. O. Roxin and published by CRC Press. This book was released on 1989-07-28 with total page 468 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Estimators for Uncertain Dynamic Systems

Download or read book Estimators for Uncertain Dynamic Systems written by A.I. Matasov and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: When solving the control and design problems in aerospace and naval engi neering, energetics, economics, biology, etc., we need to know the state of investigated dynamic processes. The presence of inherent uncertainties in the description of these processes and of noises in measurement devices leads to the necessity to construct the estimators for corresponding dynamic systems. The estimators recover the required information about system state from mea surement data. An attempt to solve the estimation problems in an optimal way results in the formulation of different variational problems. The type and complexity of these variational problems depend on the process model, the model of uncertainties, and the estimation performance criterion. A solution of variational problem determines an optimal estimator. Howerever, there exist at least two reasons why we use nonoptimal esti mators. The first reason is that the numerical algorithms for solving the corresponding variational problems can be very difficult for numerical imple mentation. For example, the dimension of these algorithms can be very high.

Book Robust Stabilization of Uncertain Systems and H    Optimal Control

Download or read book Robust Stabilization of Uncertain Systems and H Optimal Control written by Pramod P. Khargonekar and published by . This book was released on 1988 with total page 72 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Optimization in Control Applications

Download or read book Optimization in Control Applications written by Guillermo Valencia-Palomo and published by MDPI. This book was released on 2019-01-10 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue "Optimization in Control Applications" that was published in MCA

Book Control of Uncertain Dynamic Systems

Download or read book Control of Uncertain Dynamic Systems written by Shankar P. Bhattacharyya and published by CRC Press. This book was released on 2020-09-23 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collection of 34 papers presented by leading researchers at the International Workshop on Robust Control held in San Antonio, Texas in March 1991. The common theme tying these papers together is the analysis, synthesis, and design of control systems subject to various uncertainties. The papers describe the latest results in parametric understanding, H8 uncertainty, l1 optical control, and Quantitative Feedback Theory (QFT). The book is the first to bring together all the diverse points of view addressing the robust control problem and should strongly influence development in the robust control field for years to come. For this reason, control theorists, engineers, and applied mathematicians should consider it a crucial acquisition for their libraries.

Book Optimal Control

    Book Details:
  • Author : Arturo Locatelli
  • Publisher : Springer Science & Business Media
  • Release : 2001-03
  • ISBN : 9783764364083
  • Pages : 318 pages

Download or read book Optimal Control written by Arturo Locatelli and published by Springer Science & Business Media. This book was released on 2001-03 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: From the reviews: "The style of the book reflects the author’s wish to assist in the effective learning of optimal control by suitable choice of topics, the mathematical level used, and by including numerous illustrated examples. . . .In my view the book suits its function and purpose, in that it gives a student a comprehensive coverage of optimal control in an easy-to-read fashion." —Measurement and Control

Book Optimal Control

Download or read book Optimal Control written by Brian D. O. Anderson and published by Courier Corporation. This book was released on 2007-02-27 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: Numerous examples highlight this treatment of the use of linear quadratic Gaussian methods for control system design. It explores linear optimal control theory from an engineering viewpoint, with illustrations of practical applications. Key topics include loop-recovery techniques, frequency shaping, and controller reduction. Numerous examples and complete solutions. 1990 edition.

Book Optimal Control and Estimation

Download or read book Optimal Control and Estimation written by Robert F. Stengel and published by Courier Corporation. This book was released on 1994-09-20 with total page 716 pages. Available in PDF, EPUB and Kindle. Book excerpt: "An excellent introduction to optimal control and estimation theory and its relationship with LQG design. . . . invaluable as a reference for those already familiar with the subject." — Automatica. This highly regarded graduate-level text provides a comprehensive introduction to optimal control theory for stochastic systems, emphasizing application of its basic concepts to real problems. The first two chapters introduce optimal control and review the mathematics of control and estimation. Chapter 3 addresses optimal control of systems that may be nonlinear and time-varying, but whose inputs and parameters are known without error. Chapter 4 of the book presents methods for estimating the dynamic states of a system that is driven by uncertain forces and is observed with random measurement error. Chapter 5 discusses the general problem of stochastic optimal control, and the concluding chapter covers linear time-invariant systems. Robert F. Stengel is Professor of Mechanical and Aerospace Engineering at Princeton University, where he directs the Topical Program on Robotics and Intelligent Systems and the Laboratory for Control and Automation. He was a principal designer of the Project Apollo Lunar Module control system. "An excellent teaching book with many examples and worked problems which would be ideal for self-study or for use in the classroom. . . . The book also has a practical orientation and would be of considerable use to people applying these techniques in practice." — Short Book Reviews, Publication of the International Statistical Institute. "An excellent book which guides the reader through most of the important concepts and techniques. . . . A useful book for students (and their teachers) and for those practicing engineers who require a comprehensive reference to the subject." — Library Reviews, The Royal Aeronautical Society.