The present invention relates to an anti?oscillation adaptive control method for a fractional order arched MEMS resonator, and belongs to the field of anti?oscillation control. In the design process, the Chebyshev neural network with an updating single weight is used to compensate the uncertainties. The Nussbaum function is used to solve the problem of unknown control direction caused by the actuation characteris tics in Caputo fractional calculus. At the same time, a tracking differentiator based on the hyperbolic sine function is designed to solve the repeated differentiation of virtual control because of complicated fractional?order calculation. Then, under the framework of adaptive backstepping control, an anti?oscillation?based adaptive control scheme fused with Nussbaum function, neural network and tracking differentiator is developed in the framework of adaptive backstepping by means of continuous frequency distributed model. Based on the fractional order Lyapunov stability criteria, the asymptotic stability of the closed?loop system is proved. Finally, numerical simulation verifies the validity of the proposed solution.
ANTI-OSCILLATION ADAPTIVE CONTROL METHOD FOR FRACTIONAL ORDER ARCHED MEMS RESONATOR