Event-Triggered Control Strategy for Multi-Motor Systems Based on Iterative Learning

In practical applications such as multi-color printing systems, soft robotic arms and single pendulum systems, multiple motors are usually required to drive together to perform periodic tasks, but the multi-motor control process suffers from low accuracy, high computation and low reliability. To address the above problems, the periodic signals are firstly converted into repetitive signals with cycles as iterations to improve the motor position accuracy through two-dimensional control, and then the event-triggering mechanism is introduced into the control protocol to reduce the problems such as excessive information transmission and computation due to the complex structure of the multi-motor system. Finally, the stability of the proposed strategy is analyzed by using the paradigm number theory, and Matlab/Simulink is used to construct a system simulation platform to simulate the control strategy, and the results show that the number of system updates is significantly less than that of the traditional control with almost no effect on the tracking accuracy.