Integral Fuzzy Sliding Mode Controller for Hydraulic System Using Neural Network Modelling

Abstract

In this paper, a hydraulic motor controller is designed with a fuzzy supported integral sliding mode algorithm. The hydraulic system used in the study was modeled using artificial neural networks. Ability of handling nonlinearity of systems makes sliding mode controller to be a good choose for this system. The integral sliding mode controller can supply the robustness the system against the uncertainties. The basic idea of the proposed control method is to use fuzzy logic for the adaptation of the integral sliding mode control switching gain. Such adjustment reduces the chattering that is the most problem of classical sliding mode control. The equivalent control is computed using the radial basis function neural network. Simulation results of the presented method were compared with conventional PID controller results. It proved that it is more efficient to control the hydraulic system with integral fuzzy sliding mode control using neural network.