Abstract：Permanent magnet synchronous linear motor has poor speed control performance and highly depends on speed sensor. Thus, this paper designs a permanent magnet synchronous linear motor predictive current control system (MPC-MRAS) based on model reference adaptive observer. The stator voltage equation model that removes the cross-coupled electromotive force is used to predict the current controller, replacing the traditional current controller. The mathematical model of the motor itself is used as the reference model of the model prediction adaptive system, and the mathematical model of the designed output estimated current is used as the adjustable model. The motor speed is obtained by the adaptive law of the current difference design of the reference model and the adjustable model. This solution not only reduces the dependence of the current controller on motor parameters, but eliminates the influence of current coupling on the model predictive model predictive controller. At the same time, it also simplifies the complexity and cost of the control system, and improves the control performance and anti-interference ability of the control system. Simulation software is used to build predictive controllers and adaptive observers to apply to motor control systems, which verifies the superiority of the proposed control strategy. It is shown that this control strategy can realize online and accurate speed identification, and can also effectively reduce current ripple and improve current tracking performance.
李争, 安金峰, 肖宇, 张青山, 孙鹤旭. 基于自适应观测器的永磁同步直线电机模型预测控制系统设计[J]. 电工技术学报, 2021, 36(6): 1190-1200.
Li Zheng, An Jinfeng, Xiao Yu, Zhang Qingshan, Sun Hexu. Design of Model Predictive Control System for Permanent Magnet Synchronous Linear Motor Based on Adaptive Observer. Transactions of China Electrotechnical Society, 2021, 36(6): 1190-1200.
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