Intelligent Controllers in Path Tracking of a Manipulator with Bounded Disturbance Torque

摘要

Sliding mode controller (SMC) is an effective motion control strategy for robotic manipulator systems, which can ensure globally asymptotic stability. However, SMC suffer from chattering problem and a-priori knowledge of upper bound of the uncertainty is required for its effectiveness. In this paper, three main approaches naming Neural Network (NN), Fuzzy Logic (FL) and Adaptive Neuro Fuzzy Inference System (ANFIS) based adaptive intelligent SMC approach have been applied and analyzed for path tracking of a manipulator. These intelligent techniques are used to replace the signum function of sliding mode controller which results in increase of the robustness of the SMC with the elimination in the chattering. Also the maximum limit of the disturbance torque which these controllers can withstand without causing unstability has been observed. ANFIS controller has found to be the most capable to handle the maximum bounded disturbance torque; and also have the two main attractive features of minimum error and reduced chattering.