Model-free Active Disturbance Rejection Control of Two-dimensional Linear Motor Based on Multi-parameter Genetic Optimization

Abstract

The position tracking accuracy of a two-dimensional linear motor is the most important accuracy index in the servo motion process of a two-dimensional linear motor, and it is of great significance to the servo motion process of two-dimensional linear motor modeling and control. Aiming at the problem that the complex dynamic characteristics of the two-dimensional linear motor are difficult to carry out conventional mechanism modeling and other disturbances such as friction impedance during its movement a compensation scheme founded on the combination of tight format dynamic linearization model-free adaptive control and active disturbance rejection control technology is proposed, according to the data-driven control idea. The scheme provides an idea for solving the problem of friction disturbance of two-dimensional linear motors. After establishing the mathematical model of a two-dimensional linear motor, the scheme uses Matlab to simulate the algorithm. Then, owing to the influence of many adjustable parameters on the performance of the controller, and the problems of time-consuming and unsatisfactory optimization of many parameters, the controller parameters are optimized based on a genetic algorithm to improve the efficiency of parameter tuning.