Speed Synchronization Control Strategy of Dual-Motor System With Explicit Model Predictive Control

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Abstract
The synchronization ability of multi-motor system is important to the textile manufacturing and printing industries. The conventional synchronization control strategy has good steady-state performance, while its dynamic response is limited, constrained by the performance of the main controller. The model predictive controller is recognized as a controller with excellent dynamic performance. The explicit model predictive controller (EMPC) will be employed as the main controller of multi-motor system in this paper. EMPC has potential in real-time control because it can rely on offline optimization methods to avoid iterative optimization. To adapt EMPC to multi-motor systems, the unified predictive model of multi-motor drive is constructed. The multiple voltage and current constraints are simplified and all feasible control laws for multi-motor systems were successfully solved. And, an efficient binary tree polling algorithm is designed to find the optimal control law online. Meanwhile, to suppress the impact of non-ideal factors, such as load disturbance, parameter mismatch, harmonic interference, etc. on the model accuracy, the Kalman observer is designed to compensate the load disturbances and sensor errors. As verified from experimental data, the dynamic response time of EMPC has reduced to 50% of existing methods, while maintaining steady-state performance.
Funding Information
  • National Natural Science Foundation of China (51907142, 52377066)

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