Intelligent Robust Control of MEMS Gyroscopes With Initial-Condition-Independent Prescribed Performance

Abstract

In this article, the intelligent robust control with initial-condition-independent prescribed performance is addressed to control the dynamics of MEMS gyroscopes. To accurately approximate system uncertainties and disturbances resulting from the dynamic environment, the composite fuzzy learning works together with the disturbance observer. Considering the system output constraint due to the physical limits and mechanical structure, the asymmetric prescribed performance control with the time-varying initial-condition-independent barrier function is designed. To further improve the system robustness, the recursive integral terminal sliding-mode function is utilized to reduce chattering. Finally, simulations are implemented to verify that MEMS gyroscopes have the prescribed performance and higher tracking performance in the presence of uncertainties and disturbances.