Inhaltsangabe
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.
Reseña del editor
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.
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
