Optimal Adaptive Fuzzy Integral Sliding Model Control for Electrically Driven SCARA Robot Manipulator

In this paper، an optimal adaptive fuzzy integral sliding mode control is presented to control the robot manipulator position tracking in the presence of uncertainties and permanent magnet DC motor. In the proposed control، sliding surface of the sliding mode control is defined according to the information of position tracking error، derivatives، and error integral. In order to estimate bounds of the existing structured and unstructured uncertainties in the dynamics of the robot manipulator and the permanent magnet DC motor، a MIMO fuzzy adaptive approximator is designed. This helps to overcome the undesired chattering phenomenon in the control input by using fuzzy logic. Mathematical proof shows that the closed-loop system with the adaptive fuzzy integral sliding mode control in the presence of all the uncertainties has the global asymptotic stability. Furthermore، modified harmony search optimization algorithm is used to define the input coefficients of the proposed control and also to reduce the control input amplitude. In order to validate performance of the proposed controller، a case study on the SCARA robot manipulator is conducted in the presence of permanent magnet DC motor. Results of the Simulation show desired performance of the proposed controller.