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Model-Based Predictive Control: A Practical Approach (Control Series), by J.A. Rossiter
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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.
- Sales Rank: #3023177 in Books
- Brand: Brand: CRC Press
- Published on: 2003-06-27
- Original language: English
- Number of items: 1
- Dimensions: 9.21" h x .81" w x 6.14" l, 1.37 pounds
- Binding: Hardcover
- 344 pages
- Used Book in Good Condition
Most helpful customer reviews
0 of 0 people found the following review helpful.
This book helped me with Predictive Control.
By nick.a.lambert
I used this book for my dissertation and found it to be well written and very useful. I was able to implement the methods described easily enough. I would recommend this book to engineers and engineering students who are new to Model-based Predictive Control. That said, there's material in the book beyond the scope of what I needed to get a solid understanding of the basics.
0 of 2 people found the following review helpful.
very bad book on the subjcet!
By just_me
This is simply a very bad book on the subject.
First of all, the notation is not consistent and the ideas, derivations are not complete. As an example, the author considers a disturbance model d_{k+1}=d_k+v_k
but a few steps later you see that the derivation is based on the assumption that
d_{k+1}=d_k. It would be better that the author gave the book to students, his colleagues, etc to update the book.
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