Adaptive fuzzy control of MEMS gyroscope using T-S fuzzy model

In this paper, a MIMO Takagi-Sugeno (T-S) fuzzy model is built on the basis of the nonlinear model of MEMS gyroscope. The reference model is adjusted so that local linear state feedback controller could be designed for each T-S fuzzy sub-model based on parallel distributed compensation (PDC). A parameter estimation scheme for updating the parameters of T-S fuzzy models is designed and analyzed based on the Lyapunov theory. Since the derivative of the Lyapunov function is non-positive, a new adaptive law can be selected to be the former adaptive law plus a non-negative variable to guarantee that the derivative of the Lyapunov function is smaller than zero. The controller output is implemented on the nonlinear model and T-S fuzzy model at the same time. Numerical simulations are investigated to verify the effectiveness of the proposed control scheme and the correctness of the T-S fuzzy model.