An Intelligent Neuro-Fuzzy Terminal Sliding Mode Control Method With Application to Atomic Force Microscope

Abstract

In this paper, a neuro-fuzzy fast terminal sliding mode control method is proposed for controlling a class of nonlinear systems with bounded uncertainties and disturbances. In this method, a nonlinear terminal sliding surface is firstly designed. Then, this sliding surface is considered as input for an adaptive neuro-fuzzy inference system which is the main controller. A proportinal-integral-derivative controller is also used to asist the neuro-fuzzy controller in order to improve the performance of the system at the begining stage of control operation. In addition, bee algorithm is used in this paper to update the weights of neuro-fuzzy system as well as the parameters of the proportinal-integral-derivative controller. The proposed control scheme is simulated for vibration control in a model of atomic force microscope system and the results are compared with conventional sliding mode controllers. The simulation results show that the chattering effect in the proposed controller is decreased in comparison with the sliding mode and the terminal sliding mode controllers. Also, the method provides the advantages of fast convergence and low model dependency compared to the conventional methods.

Adaptive passivity-based control of an autonomous underwater vehicle

“…By comparing ( 4), (23), and substituting Hð0Þ ≡ β, τ ≡ w d ðtÞ, _ q ≡ � e v ðtÞ into (9) it can be concluded that…”

“…The SMC design is based on a converging sliding surface and guaranteed system stability by selecting proper control coefficients. 22,23 SMC is a good solution for nonlinear systems but can cause chattering phenomena in actuators, energy dissipation, and oscillating errors. Also to have a robust behavior, SMCs need the bounds of system unknown uncertainties which is a big limitation.…”