Buch, Englisch, 424 Seiten
Buch, Englisch, 424 Seiten
ISBN: 978-0-12-577240-2
Verlag: Elsevier Science & Technology
With today's competition in the high-tech industries, and the continuing need for material and energy conservation, hazard free operation, and environmentally safe discharges, it has become increasingly important todevelop and apply methodologies and techniques that lead to improved performance and operations. Process Control and Identification presents the time domain approach to modern process control, which allows for the formulation of precise performanceobjectives that can be extremized.
Important topics covered include model predictive control from an optimal control point of view, the use of state and parameter identification for implementation of optimal adaptive control, a variational approach to development of necessary conditionsfor defining optimal control problems, and the treatment of both regulatory control and time optimal control for industrial processes. Practical examples are given throughout to illustrate theoretical concepts. MATLAB, the software package that enables the solution of many optimal control problems, is used for the solution of many text examples. Computational issues as well as interpretation of results are stressed. Exercises are provided at the end of each chapter to facilitate self-study and as use as atext. With its comprehensive coverage and many examples, Process Control and Identification will be a valuable resource for practicing process control engineers and students.
Autoren/Hrsg.
Weitere Infos & Material
Basic Systems Concepts. Steady State Optimization. Dynamic Optimization. Optimal Control. The Linear Quadratic Regulator (LQR) Problem. Model Predictive Control. Robust Control. Problems Linear in the Control Variables. The Discrete Maximum Principles. State and Parameter Identification. Sequential Least Squares Parameter Estimation. The Linear Quadratic Gaussian (LQG) Problem. Appendix. Subject Index.
