The TP and TS Fuzzy model transformation based control design has revolutionized the field of control design by introducing a highly effective approach. Through the TP model transformation, it has become evident that the design of controllers and observers, as well as the effectiveness of applied LMIs, are greatly influenced by the shape of the antecedent Fuzzy sets and the number and location of the consequent systems.

Furthermore, the TP model transformation has revealed that the sensitivity of controller and observer design differs in nature. This implies that the overseer and controller design require different TS Fuzzy model representations of the system at hand. This book offers a comprehensive exploration of this phenomenon.

The book introduces several new theoretical advancements in the TP or TS Fuzzy model transformation based control design framework. It presents a complete framework for TP and TS Fuzzy model transformation and offers various tools based on this approach to enhance control design effectiveness. The book introduces novel theoretical concepts, such as interpolation between alternative TS Fuzzy model representations, which leads to a new optimization framework. It also explores methods to achieve further complexity reduction beyond rank minimization. Additionally, the book addresses the execution of TS Fuzzy model transformation for large-sized problems and demonstrates how to reinforce various properties of antecedent Fuzzy sets through manipulation.

Practical hints and guidance for control design is provided throughout the book, with examples illustrating the application of novel solutions. Matlab codes are also included to facilitate the implementation of the proposed methods.