Synopsis
This textbook provides an introduction to feedback control systems. It unifies relevant topics in a single volume. The mathematical level is that of final-year undergraduate courses in engineering, but there is minimal emphasis on technical mathematics. It provides insights to guide the design of practical systems. It should be suitable for anyone whose mathematical background includes the classical solution of ordinary differential or difference equations, the elements of probability theory and matrix algebra, as well as some confidence in manipulating mathematical expressions. A structural framework for the book is provided by three topics from applied mathematics that are regarded as providing the classical high ground of control theory: scalar, ordinary, linear dynamic equations with constant co-efficients; state space and optimal control theory in the form of dynamic programming - this being the optimization technique which offers greatest generality; and elementary probability theory, and in particular, Bayes' rule. Much of this edition has been rewritten to take account of recent developments in control theory and in how it is understood. In particular, the recognition that feedback control systems are essentially information-processing systems leads to the insight that every feedback controller must perform an information-processing function of state-estimation, that the design of a controller requires some prior information, and that the quality of achievable control depends on the quality of available information and on the manner in which it is used, as well as on characteristics of the controlled object. Features of the first edition that have been retained include the uniform treatment of both continuous-time and discrete-time systems, the provision of problems with answers and the inclusion of a wide range of topics.
Revue de presse
'the book aims to provide real insight into feedback systems and is aimed at both undergaduates and graduate students of engineering with a background in the solution of differential equations, probability theory and matrix algebra' Aslib Book Guide, Vol. 59, No. 3, March 1994
'each section is well referenced, enabling the interested reader to find a more detailed exposition elsewhere ... I felt that the author's treatment of stochastic control is the best part of the book. It is written with enthusiasm.' Peter Hydon, The Institute of Mathematics and its Applications Bulletin, Vol. 30, No. 5/6,May - June 1994
It presents basic mathematical models and tools of control theory in a way which makes it readable for undergraduate students of both mathematics and engineering. (European Mathematical Society Newsletter, No. 13, 1994)
The book provides a good introduction to the central themes of control theory. (Mathematika, 41 (1994))
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
