Sensitivity-constrained Linear Optimal Control
Author: John Robert Sesak
Publisher:
Published: 1900
Total Pages:
ISBN-13:
DOWNLOAD EBOOKRead and Download eBook Full
Author: John Robert Sesak
Publisher:
Published: 1900
Total Pages:
ISBN-13:
DOWNLOAD EBOOKAuthor: John Robert Sesak
Publisher:
Published: 1974
Total Pages: 572
ISBN-13:
DOWNLOAD EBOOKAuthor: Peter Whittle
Publisher:
Published: 1990-05-11
Total Pages: 266
ISBN-13:
DOWNLOAD EBOOKThe two major themes of this book are risk-sensitive control and path-integral or Hamiltonian formulation. It covers risk-sensitive certainty-equivalence principles, the consequent extension of the conventional LQG treatment and the path-integral formulation.
Author: Yu Feng
Publisher: Springer
Published: 2017-03-02
Total Pages: 148
ISBN-13: 9811036772
DOWNLOAD EBOOKThis book develops original results regarding singular dynamic systems following two different paths. The first consists of generalizing results from classical state-space cases to linear descriptor systems, such as dilated linear matrix inequality (LMI) characterizations for descriptor systems and performance control under regulation constraints. The second is a new path, which considers descriptor systems as a powerful tool for conceiving new control laws, understanding and deciphering some controller’s architecture and even homogenizing different—existing—ways of obtaining some new and/or known results for state-space systems. The book also highlights the comprehensive control problem for descriptor systems as an example of using the descriptor framework in order to transform a non-standard control problem into a classic stabilization control problem. In another section, an accurate solution is derived for the sensitivity constrained linear optimal control also using the descriptor framework. The book is intended for graduate and postgraduate students, as well as researchers in the field of systems and control theory.
Author: Francesco Borrelli
Publisher: Springer
Published: 2003-09-04
Total Pages: 206
ISBN-13: 3540362258
DOWNLOAD EBOOKMany practical control problems are dominated by characteristics such as state, input and operational constraints, alternations between different operating regimes, and the interaction of continuous-time and discrete event systems. At present no methodology is available to design controllers in a systematic manner for such systems. This book introduces a new design theory for controllers for such constrained and switching dynamical systems and leads to algorithms that systematically solve control synthesis problems. The first part is a self-contained introduction to multiparametric programming, which is the main technique used to study and compute state feedback optimal control laws. The book's main objective is to derive properties of the state feedback solution, as well as to obtain algorithms to compute it efficiently. The focus is on constrained linear systems and constrained linear hybrid systems. The applicability of the theory is demonstrated through two experimental case studies: a mechanical laboratory process and a traction control system developed jointly with the Ford Motor Company in Michigan.
Author: Graham Goodwin
Publisher: Springer Science & Business Media
Published: 2006-03-30
Total Pages: 415
ISBN-13: 184628063X
DOWNLOAD EBOOKRecent developments in constrained control and estimation have created a need for this comprehensive introduction to the underlying fundamental principles. These advances have significantly broadened the realm of application of constrained control. - Using the principal tools of prediction and optimisation, examples of how to deal with constraints are given, placing emphasis on model predictive control. - New results combine a number of methods in a unique way, enabling you to build on your background in estimation theory, linear control, stability theory and state-space methods. - Companion web site, continually updated by the authors. Easy to read and at the same time containing a high level of technical detail, this self-contained, new approach to methods for constrained control in design will give you a full understanding of the subject.
Author: Mansour Eslami
Publisher: Springer Science & Business Media
Published: 2013-11-09
Total Pages: 618
ISBN-13: 366201632X
DOWNLOAD EBOOKThis book provides a comprehensive treatment of the development and present state of the theory of sensitivity of dynamic systems. It is intended as a textbook and reference for researchers and scientists in electrical engineering, control and information theory as well as for mathematicians. The extensive and structured bibliography provides an overview of the literature in the field and points out directions for further research.
Author: Andrzej Wierzbicki
Publisher: Elsevier Publishing Company
Published: 1984
Total Pages: 424
ISBN-13:
DOWNLOAD EBOOKMathematical models. Sensitivity analysis of mathematical models. Optimization and optimal control. Sensitivity analysis of the optimal control systems.
Author: A. L. Dontchev
Publisher: Springer
Published: 1983
Total Pages: 170
ISBN-13:
DOWNLOAD EBOOKDevoted to current problems in sensitivity analysis of optimal control. Two topics are considered: well-posedness, i.e. continuation of the solutions; & estimation of variations in solutions of constrained optimal control problems resulting from various changes of the model.
Author: Peter Whittle
Publisher: Wiley
Published: 1996-08-01
Total Pages: 474
ISBN-13: 9780471960997
DOWNLOAD EBOOKThe concept of a system as an entity in its own right has emerged with increasing force in the past few decades in, for example, the areas of electrical and control engineering, economics, ecology, urban structures, automaton theory, operational research and industry. The more definite concept of a large-scale system is implicit in these applications, but is particularly evident in fields such as the study of communication networks, computer networks and neural networks. The Wiley-Interscience Series in Systems and Optimization has been established to serve the needs of researchers in these rapidly developing fields. It is intended for works concerned with developments in quantitative systems theory, applications of such theory in areas of interest, or associated methodology. This is the first book-length treatment of risk-sensitive control, with many new results. The quadratic cost function of the standard LQG (linear/quadratic/Gaussian) treatment is replaced by the exponential of a quadratic, giving the so-called LEQG formulation allowing for a degree of optimism or pessimism on the part of the optimiser. The author is the first to achieve formulation and proof of risk-sensitive versions of the certainty-equivalence and separation principles. Further analysis allows one to formulate the optimization as the extremization of a path integral and to characterize the solution in terms of canonical factorization. It is thus possible to achieve the long-sought goal of an operational stochastic maximum principle, valid for a higher-order model, and in fact only evident when the models are extended to the risk-sensitive class. Additional results include deduction of compact relations between value functions and canonical factors, the exploitation of the equivalence between policy improvement and Newton Raphson methods and the direct relation of LEQG methods to the H??? and minimum-entropy methods. This book will prove essential reading for all graduate students, researchers and practitioners who have an interest in control theory including mathematicians, engineers, economists, physicists and psychologists. 1990 Stochastic Programming Peter Kall, University of Zurich, Switzerland and Stein W. Wallace, University of Trondheim, Norway Stochastic Programming is the first textbook to provide a thorough and self-contained introduction to the subject. Carefully written to cover all necessary background material from both linear and non-linear programming, as well as probability theory, the book draws together the methods and techniques previously described in disparate sources. After introducing the terms and modelling issues when randomness is introduced in a deterministic mathematical programming model, the authors cover decision trees and dynamic programming, recourse problems, probabilistic constraints, preprocessing and network problems. Exercises are provided at the end of each chapter. Throughout, the emphasis is on the appropriate use of the techniques, rather than on the underlying mathematical proofs and theories, making the book ideal for researchers and students in mathematical programming and operations research who wish to develop their skills in stochastic programming. 1994