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中国物理学会期刊

基于0D物理模型与分层主动控制的霍尔推力器呼吸振荡抑制方法

Hall Thruster Breathing Oscillation Suppression Based on a 0D Physical Model and Hierarchical Active Control

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  • 采用叠加于阳极供电回路的补偿电压抑制霍尔推力器呼吸振荡,通常需要放电电流对补偿电压的响应数据,而此类数据获取成本较高,有限实验电流波形难以直接用于控制器训练与验证。为在响应数据不足条件下开展控制器训练与离线评估,本文建立一种基于双区零维模型与快慢分层控制的呼吸振荡抑制方法。首先,以实验电流的主频、均值和交流分量均方根等特征约束双区零维模型参数,并在拟合参数邻域内泛化生成物理约束的呼吸振荡样本;随后引入补偿电压到放电电流增量的局部响应模型,在上述样本基础上构造含控制响应的训练样本。在分层控制结构中,快回路生成零均值交流补偿,慢回路调整补偿起始相位、持续时间和补偿强度。多工况离线验证结果表明,该方法可在保持平均工作点基本稳定的同时,降低与呼吸振荡相关的峰峰值、交流分量均方根和频带能量。结果说明,实验特征约束下的零维模型及参数泛化可为控制器训练提供物理约束样本,提高实验电流波形的利用率。

     

    Suppressing breathing oscillations in Hall thrusters by superimposing a compensation voltage on the anode power-supply circuit generally requires discharge-current response data corresponding to the applied voltage. However, such response data are costly to obtain, and a limited number of experimental current waveforms are insufficient for direct controller training and validation. To enable controller training and offline evaluation under limited response data, this paper develops a breathing-oscillation suppression method that combines an experimentally constrained two-zone zero-dimensional (0D) model with fast-slow hierarchical active control.
    The two-zone 0D model is used to describe the dominant coupling among neutral replenishment, ionization, electron transport, wall-related losses, and discharge-current formation. Its parameters are constrained by experimental current features, including the dominant frequency, mean current, AC root-mean-square value, band energy, and cycle-shape characteristics associated with the rise and recovery stages. The experimental dataset contains 17 discharge-current waveforms covering nine power conditions. After parameter identification and waveform screening, 13 representative experimental parameter anchors are retained. Constrained domain randomization around these anchors generates 795 training samples while maintaining the experimental feature constraints. A local secondary-path model consisting of an equivalent gain, a first-order response, and a pure delay is further introduced to describe the discharge-current increment induced by the compensation voltage and to construct training samples containing control responses.
    The controller adopts a fast-slow hierarchical structure. The fast loop employs an in-phase/quadrature filtered-x least-mean-square (I/Q-FXLMS) scheme to generate zero-mean AC compensation while accounting for the secondary-path dynamics. The slow loop uses an echo state network (ESN) to extract the oscillation state from recent discharge-current measurements and a soft actor-critic (SAC) policy to adjust the starting phase, duration, and strength of the compensation. This structure separates high-frequency compensation generation from the slower adjustment of the compensation window and intensity.
    Final offline evaluation directly uses experimentally measured uncontrolled discharge-current waveforms as baseline signals. For the representative 3.5 kW condition, the controlled-to-uncontrolled ratios of the peak-to-peak current, AC root-mean-square current, and band energy are 0.580, 0.546, and 0.295, respectively. For the 13.5 kW condition, the corresponding ratios are 0.616, 0.557, and 0.307. In both cases, the spectral peaks near the dominant breathing-oscillation frequency are reduced, and the average operating point remains nearly unchanged. To further evaluate the influence of secondary-path mismatch, 323 representative response tests and 1275 full-factor tests are performed. With fixed nominal parameters, the joint pass rate in the 323 representative tests is 57.28%; after gain-and-delay correction and synchronous updating of the three secondary-path parameters, it increases to 99.07% and 99.69%, respectively, and reaches 100% when the predefined backup parameter set is enabled. In the 1275 full-factor tests, the joint pass rate is 99.76%. Only three cases fail to meet the prescribed 0.8 threshold at the combined boundary where the equivalent gain reaches 1.20 times its nominal value and the response time constant decreases to 0.70 times its nominal value.
    These results show that the experimentally constrained 0D model and constrained parameter generalization can provide physically bounded samples for controller training, while the hierarchical control structure can suppress breathing-related current fluctuations under multiple operating conditions. The offline evaluation also demonstrates the sensitivity of the control performance to local voltage-current response mismatch and identifies its finite applicability boundary, thereby providing a methodological basis for subsequent closed-loop Hall-thruster experiments.

     

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