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This book presents a comprehensive theoretical treatment of the H2 approach to data-driven control design. It features a large number of practical designs performed for different classes of processes: thermal, fluid processing and electromechanical.

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Data-Based Controller Design presents a comprehensive analysis of data-based control design. It brings together the different data-based design methods that have been presented in the literature since the late 1990´s. To the best knowledge of the author, these data-based design methods have never been collected in a single text, analyzed in depth or compared to each other, and this severely limits their widespread application. In this book these methods will be presented under a common theoretical framework, which fits also a large family of adaptive control methods: the MRAC (Model Reference Adaptive Control) methods. This common theoretical framework has been developed and presented very recently.

The book is primarily intended for PhD students and researchers - senior or junior - in control systems. It should serve as teaching material for data-based and adaptive control courses at the graduate level, as well as for reference material for PhD theses. It should also be useful for advanced engineers willing to apply data-based design. As a matter of fact, the concepts in this book are being used, under the author´s supervision, for developing new software products in a automation company. The book will present simulation examples along the text. Practical applications of the concepts and methodologies will be presented in a specific chapter.

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Definitions.- H2 Performance Criteria.- One-shot Optimization - the VRFT Method.- Interactive Optimization.- Convergence to the Globally Optimal Controller.- Cost Function Shaping.- Computations.- Experimental Results.

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