Advanced Control of Industrial Processes Structures and Algorithms [Paperback]

This book presents the concepts and algorithms of advanced industrial process control and on-line optimization within the framework of a multilayer structure. It describes the interaction of three separate layers of process control: direct control, set-point control, and economic optimization. The book features illustrations of the methodologies and algorithms by worked examples and by results of simulations based on industrial process models.

Advanced Control of Industrial Processes presents the concepts and algorithms of advanced industrial process control and on-line optimisation within the framework of a multilayer structure. Relatively simple unconstrained nonlinear fuzzy control algorithms and linear predictive control laws are covered, as are more involved constrained and nonlinear model predictive control (MPC) algorithms and on-line set-point optimisation techniques.

The major topics and key features are:

Development and discussion of a multilayer control structure with interrelated direct control, set-point control and optimisation layers, as a framework for the subject of the book.

Systematic presentation and stability analysis of fuzzy feedback control algorithms in Takagi-Sugeno structures for state-space and input-output models, in discrete and continuous time, presented as natural generalisations of well-known practical linear control laws (like the PID law) to the nonlinear case.

Thorough derivation of most practical MPC algorithms with linear process models (dynamic matrix control, generalised predictive control, and with state-space models), both as fast explicit control laws (also embedded into appropriate structures to cope with process input constraints), and as more involved numerical constrained MPC algorithms.

Development of computationally effective MPC structures for nonlinear process models, utilCH