The cooperative control of multiple permanent magnet actuators is critical to the working efficiency of the permanent magnet linear synchronous motor, so a cooperative control strategy based on the adaptive sliding model control is proposed for multiple permanent magnet actuators. The motion principle of multiple permanent magnet actuators is first introduced, and the models of thrust force are developed. Moreover, the cooperative control strategy is designed for the permanent magnet linear synchronous motor with multiple permanent magnet actuators. The adaptive sliding model control is applied to regulate the safety distance of adjacent permanent magnet actuators based on variations in speed and load. Furthermore, simulations and experiments are conducted to validate the better performances of the proposed cooperative control strategy. Experimental results indicate that the oscillation of safety distance is reduced by 33.3% when the front permanent magnet actuator is suddenly braked, the speed oscillation is mitigated by 84% when the load is imposed on the permanent magnet actuator, and the delay time caused by the sudden braking is shortened too. Therefore, the cooperative control strategy based on the adaptive sliding model control potentially improves the safety and precision of multiple permanent magnet actuators in the permanent magnet linear synchronous motor.

High precision control of angular speed of the gimbal servo system in control moment gyro is a crucial aspect of spacecraft attitude control. This article focuses on addressing the challenges posed by the problems of parameter uncertainty and mismatched disturbances in the gimbal servo system of single gimbal control moment gyro (SGCMG). To address these issues, a composite control method that combines an iterative optimal control (IOC) based on parameter identification and disturbance observer (DO) is proposed. The IOC based on parameter identification aims to suppress the problem of parameter uncertainty. Forgetting factor recursive least squares is designed to estimate the time-varying parameters of the gimbal servo system in real-time. With the results of the parameter identification, IOC algorithm is formulated to dynamically adjust the optimal control law, thereby enhancing the system's robustness and addressing the challenge of parameter uncertainty. On the other hand, the DO is designed to observe and handle the mismatched disturbances. To mitigate mismatched disturbances, coordinate transformation and feedforward compensation methods are introduced. The effectiveness of the proposed method is validated through simulations and experiments conducted on the SGCMG prototype.