Bøger af Robert Babuska

Rule-based fuzzy modeling has been recognised as a powerful technique for the modeling of partly-known nonlinear systems. It focuses on the selection of appropriate model structures, on the acquisition of dynamic fuzzy models from process measurements (fuzzy identification), and on the design of nonlinear controllers based on fuzzy models.

Focusing on the Takagi Sugeno (TS) fuzzy model, this volume provides a range of methods and tools to design observers for nonlinear systems. Readers will find an in-depth theoretic analysis accompanied by illustrative examples and simulations of real-world systems.

Rule-based fuzzy modeling has been recognised as a powerful technique for the modeling of partly-known nonlinear systems. It focuses on the selection of appropriate model structures, on the acquisition of dynamic fuzzy models from process measurements (fuzzy identification), and on the design of nonlinear controllers based on fuzzy models.