Improving the Tracking Performance under Nonlinear Time-Varying Constraints in Motion Control Applications: From Theoretical Servo Model to Experimental Validation

In the high-accuracy control of an AC machine, the knowledge of pure system parameters, with no deviation in drive coefficients and no disturbance or other nonlinear components, is a difficult issue for operators, even though it is occasionally nonviable. To overcome these troubles, this paper introduces a robust adaptation strategy based on pseudo fuzzy logic and sliding mode control (PFSMC) for an AC servo drive subject to uncertainties and/or external disturbance. Owing to the robustness of the SMC technique, the reduced sensitivity to uncertainties, and the enhanced resistance to disturbances from the pseudo fuzzy mechanism, this control algorithm can guarantee not only system stability but also the improvement of tracking errors in the steady state. To validate the design efficiency of PFSMC, both simulation and laboratory tests of the proposed scheme and a conventional PID scheme were performed to compare them as follows. In a computer environment, test cases with and without certainties were implemented with two controllers to visualize the comparative responses. Then, the two control methods were integrated into a real-world hardware platform to acquire practical outcomes. From these results, it can be noted that our successful approach showed a feasible, effective, and robust performance in AC drive.