A novel artificial intelligent control system to suppress the vibration of a FGM Plate

Abstract

In this paper, an adaptive neuro-fuzzy sliding-mode-based genetic algorithm (ANFSGA) control system is proposed to control functionally graded material (FGM) plates. The model of the FGM plate is considered by the finite element method based on the classical laminated plate theory. Moreover, to show the performance of the proposed ANFSGA intelligent control system, a traditional sliding-mode control (SMC) system and an adaptive neuro-fuzzy (ANF) SMC system are designed to suppress the vibrations of the FGM plate as a comparison. The proposed genetic algorithm control system uses the ANF SMC system in the crossover and mutation operation. In this way, the online learning ability can be used by adjusting the control parameters to deal with external disturbance. The control objective is to drive the system state to the original equilibrium point and thus, the asymptotically stability of the proposed control system can be achieved.