A novel intelligent fast terminal sliding mode control for a class of nonlinear systems: application to atomic force microscope

This paper addresses the problem of finite-time robust control using an intelligent fast terminal sliding mode control method for a class of nonlinear systems in presence of bounded uncertainty and disturbance. In the proposed method, adaptive neuro-fuzzy inference systems are utilized to determine some parameters in the nonlinear sliding surface based on the measured value of the sliding surface and the system error at each time and thereby variable nonlinear sliding surface is provided. Furthermore, an intelligent optimization algorithm namely honey bee algorithm is also applied to determine the optimal weights of the neuro-fuzzy network. Finite time convergence with increased speed and also chattering-free response are the main advantages of the proposed method compared with the conventional terminal sliding mode control methods. The proposed controller is applied to an atomic force microscope in attendance of uncertainty and disturbance. The simulation results demonstrate considerable success of the method, and show that the error reaches zero in a very short time without chattering.