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用于电荷管理中 UV LEDs 的光电热模型与模糊自适应 PID 控制

Photo-Electro-Thermal Model and Fuzzy Adaptive PID Control for UV LEDs in Charge Management.

机构信息

Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China.

University of Chinese Academy of Sciences, Beijing 100049, China.

出版信息

Sensors (Basel). 2023 Jun 27;23(13):5946. doi: 10.3390/s23135946.

Abstract

Inertial sensors can serve as inertial references for space missions and require charge management systems to maintain their on-orbit performance. To achieve non-contact charge management through UV discharge, effective control strategies are necessary to improve the optical power output performances of UV light sources while accurately modeling their operating characteristics. This paper proposes a low-power photo-electro-thermal model for widely used AlGaN-based UV LEDs, which comprehensively considers the interaction of optical, electrical, and thermal characteristics of UV LEDs during low-power operations. Based on this model, an optical power control system utilizing a fuzzy adaptive PID controller is constructed, in which a switch is introduced to coordinate the working state of the controller. Thus, the steady-state performance is effectively improved while ensuring dynamic performance. The results show that the proposed model has an average prediction error of 5.8 nW during steady-state operations, and the fuzzy adaptive PID controller with a switch can reduce the fluctuation of light output to 0.67 nW during a single discharge task, meeting the charge management requirements of high-precision inertial sensors.

摘要

惯性传感器可用作空间任务的惯性基准,需要电荷管理系统来维持其在轨性能。为了通过紫外线放电实现非接触式电荷管理,需要有效的控制策略来提高紫外线光源的光功率输出性能,同时准确建模其工作特性。本文提出了一种用于广泛使用的基于 AlGaN 的 UV LED 的低功耗光电热模型,该模型综合考虑了 UV LED 在低功率工作时的光学、电学和热特性的相互作用。基于该模型,构建了一个利用模糊自适应 PID 控制器的光功率控制系统,其中引入了一个开关来协调控制器的工作状态。因此,在确保动态性能的同时,有效地提高了稳态性能。结果表明,所提出的模型在稳态运行时的平均预测误差为 5.8 nW,具有开关的模糊自适应 PID 控制器可以将单次放电任务中的光输出波动降低到 0.67 nW,满足高精度惯性传感器的电荷管理要求。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da4d/10346610/d37a26b0bd18/sensors-23-05946-g001.jpg

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