Robust Industrial Control Systems: Optimal Design Approach for Polynomial Systems - Hardcover

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Professor Michael Grimble, Director of the Industrial Control Centre and Past Chairman of the Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow, UK

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Robust Industrial Control Systems: Optimal Design Approach for Polynomial Systems presents a comprehensive introduction to the use of frequency domain and polynomial system design techniques for a range of industrial control and signal processing applications. The solution of stochastic and robust optimal control problems is considered, building up from single-input problems and gradually developing the results for multivariable design of the later chapters. In addition to cataloguing many of the results in polynomial systems needed to calculate industrial controllers and filters, basic design procedures are also introduced which enable cost functions and system descriptions to be specified in order to satisfy industrial requirements.

Providing a range of solutions to control and signal processing problems, this book:

• Presents a comprehensive introduction to the polynomial systems approach for the solution of H₂ and H₈ optimal control problems.
• Develops robust control design procedures using frequency domain methods.
• Demonstrates design examples for gas turbines, marine systems, metal processing, flight control, wind turbines, process control and manufacturing systems.
• Includes the analysis of multi-degrees of freedom controllers and the computation of restricted structure controllers that are simple to implement.
• Considers time-varying control and signal processing problems.
• Addresses the control of non-linear processes using both multiple model concepts and new optimal control solutions.

Robust Industrial Control Systems: Optimal Design Approach for Polynomial Systems is essential reading for professional engineers requiring an introduction to optimal control theory and insights into its use in the design of real industrial processes. Students and researchers in the field will also find it an excellent reference tool.