Adaptive robust control based on T-S fuzzy-neural systems for a hypersonic vehicle

This paper proposes a on-line modeling and control approach through Takagi-Sugeno (T-S) fuzzy-neural model for a class of generalized multiple input multiple output (MIMO) nonlinear dynamic systems with external disturbances. Nonlinear systems are exactly formed a linearized system via the mean value theroem, and then the T-S fuzzy-neural model can approximate the linearized system. Then on-line identification algorithm and an adaptive scheme are used on tracking controller design. A hypersonic vehicle is modeled and attitude controller is designed using the proposed method. Simulation results on guidance, navigation and control (GNC) platform show a satisfactory performance for the attitude tracking.