Design of nonlinear adaptive interaction algorithm controller for improvement of tracking performance of X-Y table ball screw drive system - Retas, Zain (2023)
Recently, the main interest in machine tools are to obtain precise positioning, robust tracking, low-cost manufacturing as well as adaptivity towards disturbances. These recent requirements or paradigm shift have led to a new and challenging era in the area of machining tools and control. However, the presence of disturbances during machining processes in the form of cutting forces and friction forces have greatly reduced positioning and tracking accuracy of the system. Basically, there are three main objectives in this thesis. Firstly, to identify the mathematical model of machine tool for XY table using system identification technique through frequency response function (FRF) of the system. Secondly is to design a new control strategy that will provide good tracking performance of the XY table. The final objective is to validate the proposed technique through simulation using MATLAB/Simulink software and experimental work using real plant of Googoltech XY table. The methodology of this research is conducted based on the set objectives. This thesis proposes one new approach and contribution to compensate cutting force disturbances. The contribution is Nonlinear Adaptive Interaction Algorithm (NAIA). The controller is developed based on the enhancement and modification of the basic Adaptive Interaction Algorithm Controller (AIA). The NAIA controller is designed by integrating a modified nonlinear function to the base AIA controller. This thesis has successfully demonstrated that the tracking performance of a machine tool was increased significantly through the newly proposed technique that was compared with the basic PID controller. Results showed that the newly proposed NAIA control strategy managed to provide up to 60.2% improvement in comparison with PID (frequency, f = 0.6 Hz) and 53.55% improvement in comparison with CasPAi (at f = 0.2 Hz). In addition, results showed that the NAIA provides an improvement of 86.29% in terms of Root Mean Square Error (RMSE) for f = 0.6 Hz in comparison with PID and 78.68% improvement in comparison with CasPAi. However, further improvements are still needed. It is recommended for future work; the compensation of friction forces should be considered so that it enables further reduction of the tracking error especially in the segment of quadrant glitch.