Cascade Optimal Control for Tracking and Synchronization of a Multimotor Driving System

Abstract

This brief investigates the optimal control design for a multimotor driving system (MDS). Since the dynamic characteristic of MDS is multivariable, high order, strong coupling, and nonlinear, it is difficult to design an appropriate control framework to simultaneously achieve the load tracking and multimotor synchronization. By dividing the MDS into a load subsystem and a multimotor subsystem, a novel cascade optimal control framework including outer and inner loops is proposed. In this framework, the optimal-tracking controller (OTC) and the optimal synchronization controller (OSC) can be designed individually by decomposing a comprehensive performance index. In order to construct the OTC, the backstepping approach is incorporated into the optimal control to make the load track a reference command; then, the OSC is developed via the mean deviation coupling control strategy to guarantee that all the motors’ states can converge their average value. In addition, the state and extended disturbance observers are combined with OTC and OSC to deal with the immeasurable states and the system uncertainties. The proposed control framework not only addresses the optimal control problems of the load tracking and multimotor synchronization but also has a strong robustness to the system uncertainties. The Lyapunov theory proves that all signals in the closed-loop system are ultimately uniformly bounded. Practical experiments based on a four-motor driving system are conducted to validate the efficiency of the proposed control framework.