This paper develops delay-independent fuzzy hyperbolic guaranteed cost control for nonlinear continuous-time systems with parameter uncertainties. Fuzzy hyperbolic model (FHM) can be used to establish the model for ce...This paper develops delay-independent fuzzy hyperbolic guaranteed cost control for nonlinear continuous-time systems with parameter uncertainties. Fuzzy hyperbolic model (FHM) can be used to establish the model for certain unknown complex system. The main advantage of using FHM over Takagi-Sugeno (T-S) fuzzy model is that no premise structure identification is needed and no completeness design of premise variables space is needed. In addition, an FHM is not only a kind of valid global description but also a kind of nonlinear model in nature. A nonlinear quadratic cost function is developed as a performance measurement of the closed-loop fuzzy system based on FHM.Based on delay-independent Lyapunov functional approach, some sufficient conditions for the existence of such a fuzzy hyperbolic guaranteed cost controller via state feedback are provided. These conditions are given in terms of the feasibility of linear matrix inequalities (LMIs). A simulation example is provided to illustrate the design procedure of the proposed method.展开更多
文摘This paper develops delay-independent fuzzy hyperbolic guaranteed cost control for nonlinear continuous-time systems with parameter uncertainties. Fuzzy hyperbolic model (FHM) can be used to establish the model for certain unknown complex system. The main advantage of using FHM over Takagi-Sugeno (T-S) fuzzy model is that no premise structure identification is needed and no completeness design of premise variables space is needed. In addition, an FHM is not only a kind of valid global description but also a kind of nonlinear model in nature. A nonlinear quadratic cost function is developed as a performance measurement of the closed-loop fuzzy system based on FHM.Based on delay-independent Lyapunov functional approach, some sufficient conditions for the existence of such a fuzzy hyperbolic guaranteed cost controller via state feedback are provided. These conditions are given in terms of the feasibility of linear matrix inequalities (LMIs). A simulation example is provided to illustrate the design procedure of the proposed method.
