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Multi-Permanent Magnet Synchronous Motor Speed Consensus Control Based on Prescribed Performance Control |
Li Taochang, Cong Shuyuan, Hou Limin |
Faculty of Electrical and Control Engineering Liaoning Technical University Huludao 125105 China |
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Abstract In the multi-permanent magnet synchronous motor (multi-PMSM), the speed regulation system’s speed synchronization accuracy is critical for production efficiency and equipment stability. To enhance the performance of coordinated speed control in multi-motor systems, this paper proposes a speed consensus control method for multi-PMSM systems based on prescribed performance control (PPC). Multi-agent systems (MAS) collaborative control, owing to its architectural flexibility, system reconfigurability, and inherent distributed robustness, has shown significant potential in collective decision- making and coordinated optimization for complex industrial systems. Given the marked resemblance between multi-PMSMs coordinated speed regulation mechanisms and MAS collaborative control, this paper innovatively introduces the MAS consensus control paradigm into speed consensus control of multi-PMSMs. Specifically, by conceptualizing each PMSM speed regulation system as an agent and establishing information exchange among motor speed control systems through communication topology networks, the multi-PMSM speed synchronization challenge is transformed into a MAS consensus control problem. A distributed consensus control protocol is designed to guarantee speed coordination convergence across multiple PMSMs. The paper first formulates the speed consensus control problem for multi-PMSM systems within the theoretical framework of MAS. Subsequently, a PPC-based consensus control protocol is designed for the multi-PMSMs speed consensus control system, in which explicit constraints on transient and steady-state processes are predefined to improve synchronization. Concurrently, a super-twisting extended state observer (STESO) is introduced to estimate system disturbances, with real-time compensation integrated into the consensus control protocol, thereby significantly improving closed-loop robustness. Comparative experimental verification is conducted on a multi-motor speed regulation and loading comprehensive experimental platform under diverse operating conditions. The experimental protocol includes (1) speed increase and decrease, (2) load addition and subtraction, and (3) forward and reverse rotation. The acceleration and deceleration experiments demonstrate that the proposed method achieves a steady-state amplitude of approximately 0.5 r/min during steady-state operation. The PI-enhanced relative coupling control (RCC) method is around 5 r/min. The tracking error amplitude of the proposed method is approximately 0.8 r/min, significantly smaller than that of the RCC method. Furthermore, the synchronization error amplitudes before and after speed ramping are around 0.8 r/min and 1 r/min, respectively, whereas the RCC method’s synchronization error amplitudes are 6 r/min and 8 r/min. The load variation experiments demonstrate that under the proposed control scheme, the speed variation is approximately 32 r/min when different loads are applied at various times and around 38 r/min when the same load is applied simultaneously. The speed quickly recovers to 300 r/min, with post-recovery tracking and synchronization errors maintained at about 2 r/min. In contrast, under the RCC method, the speed variation is 35 r/min for different loads and approximately 42 r/min for the same load, with post-recovery tracking and synchronization errors around 5 r/min. The forward and reverse experiments show that the proposed method’s stable tracking and synchronization errors are approximately 0.8 r/min, significantly lower than the errors of roughly 5 r/min with the RCC method. The proposed method effectively achieves speed consensus control in multi-PMSM regulation systems, demonstrating significant improvements in synchronization accuracy, flexibility, and robustness against external disturbances.
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Received: 10 December 2024
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