High-Quality Positioning Strategy for Biaxial Contour Machining System With Nonlinear Model Predictive Control
Zhanqing Zhou, Senkai Zhang, Zhengchao Xu, Ying Peng, Xuefeng Jin
Abstract
The trajectory tracking ability is an important index to measure the computer numerical control (CNC) machining tools. In this article, the nonlinear model predictive control strategy (NMPC) is proposed to improve the trajectory tracking ability of the biaxial contour machining system (BCMS). The position-, velocity-, and current-loop of the permanent magnet synchronous motors (PMSMs) of the BCMS are considered as the complete control object to construct a single-loop nonlinear model predictive controller. Meanwhile, the matching nonlinear disturbance observer (NL-DOB) is designed to estimate the uncertainty disturbances caused by the parameters mismatch, external load changes, and harmonic disturbances in real time. And the estimated disturbance values are used as feed-forward compensations, which can improve the steady-state performance of the system. Finally, the positioning performance comparison between the proposed strategy and the conventional ones is carried out on the testbench. The experimental results indicate that the positioning errors can be reduced by up to 40% with the proposed algorithm.