Adaptive vibration control of microelectromechanical systems triaxial gyroscope using radial basis function sliding mode technique

Abstract

In this article, a novel radial basis function neural network adaptive sliding mode control is developed for the tracking control of microelectromechanical systems triaxial gyroscope. The advantages of the adaptive control, neural network control and sliding mode control are combined together to implement the control task. Switching function and sliding mode controller are utilized as the input and output of the radial basis function neural network, respectively. The proposed adaptive neural sliding mode control has on-line learning ability to deal with system nonlinearities by adjusting the control parameters updated from the Lyapunov analysis. Simulation studies are investigated to verify the effectiveness of the proposed adaptive neural sliding mode control scheme.