Region maximization technique in robust nonlinear control via state-dependent scaling design

This paper focuses on the state-dependent scaling design for robust nonlinear control and proposes a unified computational approach to nonlinear controller design. The approach seeks a controller maximizing the region of stability instead of maximizing locally-allowable uncertainty size. This paper shows how to formulate problems of region maximization as convex and nonconvex optimization problems. A global optimization algorithm is proposed to solve the nonconvex problem. This paper proposes a novel design procedure which bridges the gap between the computational technique for unspecific nonlinear systems and global stabilization techniques for analytically tractable nonlinear systems.