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Process Control and Identification
Process Control and Identification
Author:
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 Identificati... more » 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.
Variational approach to process optimal control
Comprehensive treatment of optimal regulatory control including measurable, unmeasurable, and partially measurable load disturbances
Treatment of optimal process control problems linear in the control variables leading to bang-bang control laws
Presents discrete optimal control problems important to computer control algorithms
Develops process identification algorithms from a variational perspective
Use of sequential least squares for parameter identification.
Applications of the linear quadratic Gaussian problem (LQG) for the adaptive control of uncertain processes
Illustrative practical process examples throughout the text, many using MATLAB(r) software
Over 60 exercises to facilitate self-study and use as a text
Author:
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 Identificati... more » 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.
Variational approach to process optimal control
Comprehensive treatment of optimal regulatory control including measurable, unmeasurable, and partially measurable load disturbances
Treatment of optimal process control problems linear in the control variables leading to bang-bang control laws
Presents discrete optimal control problems important to computer control algorithms
Develops process identification algorithms from a variational perspective
Use of sequential least squares for parameter identification.
Applications of the linear quadratic Gaussian problem (LQG) for the adaptive control of uncertain processes
Illustrative practical process examples throughout the text, many using MATLAB(r) software
Over 60 exercises to facilitate self-study and use as a text
ISBN-13: 9780125772402
ISBN-10: 0125772408
Publication Date: 11/11/1993
Pages: 424
Rating: ?
ISBN-10: 0125772408
Publication Date: 11/11/1993
Pages: 424
Rating: ?
0 stars, based on 0 rating
Genres:
- Science & Math >> Mathematics >> General
