Robot Trajectory Tracking Control Based On T-S Fuzzy Model

Robot system is a complex nonlinear system with multi-input and multi-output and strong coupling. The nonlinear and uncertainties in robot dynamical equations include parametric uncertainties, unknown disturbances and un-modeled dynamics. T-S fuzzy model and sliding mode control are effective ways to deal with the nonlinear and uncertain system.The acquisition of T-S fuzzy model is not required to establish accurate system models and it can approximate nonlinear and uncertainty terms in any precision. The sliding mode state of nonlinear system is relatively independence with system parameter perturbation and external disturbance,which result in a strong inhibitory effect to robot system’ uncertainty. For the sake of high nonlinear and uncertainty in robot system, algorithms are suitable for robot system can be extended to other complex nonlinear systems. Therefore, the study of this article has some theoretical and practical significance, the main contents are as follow:1) In order to inhibit changing of nonlinear uncertain robot system’s parameters, we deal the system model by sector nonlinearity, and designed a PD controller based on T-S fuzzy model by its characteristic of approximates nonlinear system. Then the method verified by trajectory tracking in Matlab platform.2) In order to eliminate the error from T-S fuzzy model approximate real model, we designed a sliding mode controller by its’advantage of suppress robot system’uncertainties, then designed a robot sliding mode controller, which based on T-S fuzzy model, its makes the robot system has the T-S fuzzy model’ability of approximating robot real model and sliding mode controller’ strong robust to uncertainty systems. Then we employed simulation in matlab simulation platform, verified the correctness and effectiveness of the method.