Model predictive and compensated ADRC for permanent magnet synchronous linear motors

Area of Science:

• Control Engineering
• Robotics
• Mechatronics

Background:

• Traditional linear active disturbance rejection control (LADRC) struggles with rapid and precise disturbance rejection in permanent magnet synchronous linear motors (PMSLMs).
• Uncertainties and external disturbances significantly impact PMSLM performance, necessitating advanced control strategies.

Purpose of the Study:

• To propose a novel Model Predictive and Compensated Linear Active Disturbance Rejection Control (MP-LADRC) method for PMSLMs.
• To enhance the speed and precision of disturbance rejection and motion control in PMSLMs.

Main Methods:

• A Model Compensated Extended State Observer (MESO) was designed to create a compensated mathematical model of the PMSLM by addressing total disturbance.
• A phase advance module was integrated with MESO to accelerate the estimation of system states and disturbances, enabling real-time compensation.
• A Model Predictive Controller (MPC) was designed based on the compensated model to further mitigate unobserved disturbances via an optimal control law derived from a quadratic objective function.

Main Results:

• The proposed MESO effectively compensated for system uncertainties and disturbances in real-time.
• The integrated phase advance module improved the estimation speed of MESO.
• The MP-LADRC method demonstrated superior rapid anti-disturbance capabilities and fast positioning accuracy in simulations and experiments.

Conclusions:

• The MP-LADRC method offers a dual-degree-of-freedom disturbance rejection mechanism through the synergistic action of MESO and MPC.
• The proposed control strategy significantly enhances the performance of PMSLM motion control systems, particularly in terms of anti-disturbance and positioning.
• The MP-LADRC method provides a viable and effective solution for demanding motion control applications involving PMSLMs.