Fixed-Time Fuzzy Vibration Reduction for Stochastic MEMS Gyroscopes with Low Communication Resources

The microelectromechanical system (MEMS) gyroscope is a complex nonlinear system with multiple variables, strong coupling, and susceptibility to stochastic disturbances. This paper presents an adaptive fuzzy control scheme for stochastic MEMS gyroscopes, with the primary objectives of reducing control vibration and achieving high precision prescribed performance tracking with low communication resources within a fixed-time backstepping framework. To address the stochastic disturbances and unknown nonlinear system dynamics, the interval type-3 fuzzy logic system (IT3FLS) is introduced. Additionally, a novel quadratic prescribed performance function (QPPF) is proposed to ensure satisfactory transient and steady-state performance of the system while mitigating initial control vibrations during fast error convergence. Furthermore, an event-triggered mechanism (ETM) is developed using a switching threshold strategy to minimize the communication load without compromising control accuracy. By utilizing the fixedtime command-filtered backstepping design method and newly introduced error-compensating signals, the issue of “explosion of complexity” is effectively resolved, and filtering errors are adequately compensated. The proposed control scheme guarantees that the tracking errors converge to a predefined set of arbitrarily small residuals in probability. In addition, all the closed-loop signals are within a fixed time bounded in probability (FTBIP). The simulation results validate the effectiveness and superiority of the proposed scheme.