Gain-scheduled flight control law design using a new fuzzy clustering technique

In this paper a gain scheduling methodology is proposed, which exploits a fuzzy modeling technology based on quasi-linear parameter varying (QLPV) description of a nonlinear model of a missile, to resolve two main deficiencies of classical gain scheduling approaches (restriction to near equilibrium operation and lack of a satisfactory interpolation mechanism). A new clustering approach (designated as fuzzy clustering based classification trees: FC²T) is employed in fuzzy modeling. It is shown that employment of FC²T in the development of fuzzy model for the system produces a lower estimation error than Gustafson-Kessel fuzzy clustering and a tree partitioning algorithm, while it does not confront by randomly initialization problem. Merits of the proposed fuzzy model-based gain scheduling technique are demonstrated in a demanding application. Simulation studies are reported to demonstrate the stability, the performance and the robustness of the designed fuzzy controller.