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Event-based disturbance compensation control for discrete-time SPMSM with mismatched disturbances

机译:基于事件的扰动补偿控制,用于离散时间SPMSM具有不匹配的干扰

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This paper investigates the problem of event-based disturbance compensation control for discrete-time surface-mounted permanent magnet synchronous motor (SPMSM) subject to both mismatched external disturbances and the limited communication bandwidth. The mismatched external disturbances make it impossible to transform the original model into the multiple-step-ahead predictor model by using the existing predictor technology. To tackle such a challenge, a novel backstepping-based disturbance compensation control framework is firstly proposed for the discrete-time SPMSM with known system dynamics. In the proposed framework, the disturbance observer is designed to compensate for the external disturbances, and the novel variable substitution/decoupling technology is proposed to design the event-based controller for the original controlled system. The proposed controller is composed of the event-based feedback control signal and the feedforward disturbance compensation signal, thereby improving the system disturbance rejection ability and mitigating the communication resource. Subsequently, an event-based adaptive neural control scheme is proposed by combining a modified neural disturbance observer. The proposed scheme ensures that the tracking error converges to a small neighbourhood of the origin, all the signals in the closed-loop system are bounded and meanwhile the communication resources are greatly reduced. The effectiveness of the proposed controller is illustrated through the simulation results.
机译:本文研究了基于事件的扰动补偿控制的问题,用于离散时间安装的永磁同步电动机(SPMSM),其经受不匹配的外部干扰和有限的通信带宽。不匹配的外部干扰使得不可能通过使用现有的预测器技术将原始模型转换为多步预测仪模型。为了解决这种挑战,首先提出了一种新的基于BackStepping的扰动补偿控制框架,用于具有已知系统动态的离散时间SPMSM。在所提出的框架中,扰动观察者旨在补偿外部干扰,并提出了新的可变替代/去耦技术来设计原始受控系统的基于事件的控制器。所提出的控制器由基于事件的反馈控制信号和前馈干扰补偿信号组成,从而改善了系统干扰抑制能力并减轻了通信资源。随后,通过组合改进的神经扰动观测器来提出基于事件的自适应神经控制方案。所提出的方案确保了跟踪误差会聚到原点的小邻域,闭环系统中的所有信号都是界限的,同时通信资源大大减少。通过仿真结果说明了所提出的控制器的有效性。

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