Active Disturbance Rejection Based Repetitive Learning Control With Applications in Power Inverters
Active Disturbance Rejection Based Repetitive Learning Control With Applications in Power Inverters
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DOI：
10.1109/tcst.2020.3028219
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发表时间：
2021-09
影响因子：
4.8
通讯作者：
Qi Meng;Z. Hou
中科院分区：
文献类型：
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作者：
Qi Meng;Z. Hou
研究了一种新的基于自抗扰的重复学习控制方案，包括前馈、反馈和抗扰三个通道。这项工作的目标是实现高品质的输出电压和鲁棒性的干扰和逆变器系统中的不确定性。在设计控制器时，将逆变器的数学模型用两个积分器组成的链来代替，避免了模型辨识和时变参数估计。忽略的系统动态，不确定性，以及由非重复性干扰引起的非重复性因素都被定义为要估计和补偿的总干扰的一部分，这降低了控制器对系统参数和操作环境的灵敏度。分析了控制系统方案沿着周期的稳定性条件，并在频谱上证明了组合控制方案对不同频带干扰的抑制作用。最后，在硬件平台上对算法进行了验证，并测试了对不同参数的耐受性。
A novel active disturbance rejection based repetitive learning control scheme, including three channels, namely, feedforward, feedback, and disturbance rejection channels, is investigated. The goal of this work is to achieve a high-quality output voltage and robustness to disturbances and uncertainties in the inverter system. The mathematics model of the inverter is replaced by a chain of two integrators to avoid model identification and time-varying parameter estimation when designing the controller. The ignored system dynamics, the uncertainties, and the nonrepetitive factors caused by nonrepetitive disturbances are all defined as part of the total disturbance to be estimated and compensated for, which decreases the controller sensitivity for the system parameters and operating environment. The stability conditions of the control system scheme along the periods are analyzed, and the mitigation of different frequency-band disturbances using the combination control scheme is demonstrated on the frequency spectrum. Finally, the algorithm is validated on a hardware platform, and the tolerability of varying parameters is tested.