Robust Optimal State-Feedback Controllers Design of Uncertain Nonlinear Dynamic Systems by Using Integrative Optimization Approach

This paper considers the design problem of the robust optimal state-feedback controllers for the uncertain nonlinear dynamic systems, where the uncertain nonlinear dynamic systems can be represented by the Takagi-Sugeno (TS) fuzzy-model-based dynamic systems with both elemental parametric uncertainties and norm-bounded approximation error. An integrative method, which complementarily fuses the robust stabilizability condition, the orthogonal-functions approach (OFA) and the hybrid Taguchi-genetic algorithm (HTGA), is presented in this paper to design the robust quadratic-optimal state-feedback controllers, in which the robust stabilizability condition is proposed in terms of linear matrix inequalities (LMIs). A design example is given to demonstrate the applicability of the proposed integrative optimization approach.