Multimotor Synchronous and Antidisturbance Control for Two-Stage Friction Wheels Launcher

The purpose of this article is to propose a model predictive repeated learning (MPRL) control strategy to achieve high-performance control of the multimotor servo control (MMSC) system. The control strategy generates feedforward by learning the synchronization uncertainty between motors, reduces the synchronization error between motors, and improves the synchronization of the MMSC system. High-precision speed tracking is achieved through state prediction, and energy constraints are incorporated into the controller to reduce energy loss in the MMSC system. The trigger mode and input distribution are used to compensate for the impact on the system, and stable speed tracking and synchronization of the MMSC system under impact disturbances are achieved. Finally, a composite control scheme is obtained. Compared with conventional methods, the MPRL method can handle synchronization uncertainty, compensate for disturbances caused by shocks, and simultaneously obtain high-precision speed tracking and speed synchronization between motors. A research prototype of the two-stage launcher system is developed, and experimental setup is constructed. The experimental results show the effectiveness of the MPRL method and its advantages compared with conventional methods.