A new type-3 fuzzy predictive controller for MEMS gyroscopes

This study presents a new nonlinear model-based predictive control scheme using fractional-order calculus and interval type-3 (IT3) fuzzy logic systems (FLSs) for Micro-Electro-Mechanical-System gyroscopes (MEMS-Gs). The dynamics of MEMS-G are unknown and perturbed by actuator faults and disturbances. Two IT3-FLSs are used for online modeling of uncertainties and predicting of tracking error. The IT3-FLSs are online optimized by Lyapunov adaptation rules such that the stability and robustness to be guaranteed. Also, the designed compensators adaptively tackle the effects of perturbations and estimation errors. In various conditions such as dynamic perturbations, actuator nonlinearities, tracking of a chaotic system, and tracking of a pulse signal with sharp rising and falling, we examine the capability of the suggested controller and compare with new controllers and other type of FLSs. We show that a well tracking accuracy with the desired transient performance and least overshoot is obtained.

Automated summary

This study proposes a new nonlinear model-based predictive control scheme using fractional-order calculus and interval type-3 fuzzy logic systems for controlling MEMS-Gs. The controller demonstrates effectiveness in handling dynamic perturbations, actuator nonlinearities, and tracking of chaotic systems.