Dynamical analysis and accelerated adaptive backstepping funnel control for dual-mass MEMS gyroscope under event trigger

This paper investigates an adaptive backstepping funnel control scheme with an event-triggered mechanism for a chaotic dual-mass Micro-Electro-Mechanical Systems (MEMS) gyroscope. The mathematical model of the dual-mass micro-gyroscope is first developed based on a mutual mechanical coupling. Then, its inherent nonlinear characteristics under different spring and coupling coefficients, all of which have noticeable impacts on the system sensitivity, are fully examined through phase and Lyapunov exponent diagrams. In order to methodically address the control problem involving the uncertainty, the slow convergence, the constraint violation, the “item explosion” and the communication resource waste, an accelerated adaptive backstepping funnel controller is proposed by combining the type-2 sequential fuzzy neural network (T2SFNN), the speed function, the asymmetric funnel boundaries, the accelerated exponential integral tracking differentiator (AEITD) and the event-triggered mechanism. The recommended scheme not only well resolve the above issues, but also guarantee the prescribed performance requirements and the boundedness of all signals in closed-loop system. Finally, the effectiveness of the control scheme is substantiated through several simulated results.