Adaptive Neural Network Control Method For Arch-Shaped Microelectromechanical System

摘要

#$%^&*AU2018100710A420180628.pdf#####ABSTRACT The present disclosure discloses an adaptive neural network control method for an arch-shaped microelectromechanical system. The method includes: a step (a) of constructing a system model of an arch-shaped microelectromechanical system based on an Euler-Bernoulli beam; and a step (b) of constructing an adaptive neural network controller for suppressing chaotic oscillations of the arch-shaped microelectromechanical system and ensuring state constraints of the system; and when the controller is constructed, ensuring an unviolated output constraint of the arch-shaped microelectromechanical system using a symmetric barrier Lyapunov function, adopting a RBF neural network having an adaptive rule to estimate an unknown nonlinear function with an arbitrarily small error, introducing an extended state tracking differentiator to address a problem of repeated derivative calculations required for a virtual control item in a backstepping control, designing a state observer to obtain immeasurable state information, and fusing the extended state tracking differentiator and the state observer in a backstepping framework. The present disclosure is convenient for an analysis and proof of a stability, and has characteristics including a low requirement on modeling accuracy, a low calculation complexity, a quick arithmetic speed, a good operation stability of the system, and high motion accuracy.1/9 vaibl -~ variable X o Cd rl Cd4 0 C , 4 -.--. oil Cd1 4 I cn