Model-Based Predictive Control: A Practical Approach

J.A. Rossiter, J.A. Rossiter

June 27, 2003 by CRC Press
Textbook - 344 Pages - 67 B/W Illustrations
ISBN 9780849312915 - CAT# 1291
Series: Control Series

USD$132.95

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Features

  • Provides extensive insight into the connection between optimal control and stability
  • Examines the closed loop paradigm, a beneficial structure in the use of MPC
  • Identifies the implementation of MPC using small computational burdens
  • Details the use of implicit modelling for MPC, a subject not addressed in any other book
  • Directs readers via route maps to specific areas of interest; summary boxes used to deliver a quick snapshot of key results
  • Summary

    Model Predictive Control (MPC) has become a widely used methodology across all engineering disciplines, yet there are few books which study this approach. Until now, no book has addressed in detail all key issues in the field including apriori stability and robust stability results. Engineers and MPC researchers now have a volume that provides a complete overview of the theory and practice of MPC as it relates to process and control engineering.

    Model-Based Predictive Control, A Practical Approach, analyzes predictive control from its base mathematical foundation, but delivers the subject matter in a readable, intuitive style. The author writes in layman's terms, avoiding jargon and using a style that relies upon personal insight into practical applications.

    This detailed introduction to predictive control introduces basic MPC concepts and demonstrates how they are applied in the design and control of systems, experiments, and industrial processes. The text outlines how to model, provide robustness, handle constraints, ensure feasibility, and guarantee stability. It also details options in regard to algorithms, models, and complexity vs. performance issues.

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