执行器退化情况下基于逆变器资源的人在回路弹性控制
Human-on-the-loop Resilient Control of InverterBased Resources Under Actuator Degradation
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中文总结 AI 辅助
研究执行器退化时基于逆变器资源的控制问题，提出人在回路弹性控制框架，嵌入人类监督判断，引入发电备用容量和受控性能退化两个指标及调整参数μ，经稳定性分析与仿真验证，该架构在控制储备、防止执行器饱和及电压调节方面表现更优。
中文摘要 AI 辅助
本文提出了一种用于在执行器退化情况下运行的基于逆变器的电网支持资源（IBR）的人在回路弹性控制架构。传统的容错控制和自适应控制策略在此场景中各有显著局限性。为克服这些限制，所提框架将人类监督判断直接嵌入控制回路。提出了两个新指标：发电备用容量（GRC）和受控性能退化（CPD）。通过人选择的弹性调整参数μ来权衡即时跟踪精度和长期运行准备状态。给出了所提人在回路μ模自适应控制器的稳定性分析。通过对并网逆变器在连续执行器退化下的仿真验证了该方法，结果表明所提架构保留了控制储备，防止了执行器饱和，并实现了优于传统自适应控制和容错控制方法的电压调节。
英文摘要
This paper proposes a human-on-the-loop resilient control architecture for grid-supporting inverter-based resources (IBRs) operating under actuator degradation. Conventional fault-tolerant control and adaptive control strategies each face notable limitations in this setting: active FTC depends on fast, accurate fault detection and isolation, leaving it vulnerable to misdiagnosis of incipient or ambiguous degradation, while passive FTC tends toward overly conservative operation. Adaptive controllers face a related problem as they typically assume sufficient control authority, but when actuator degradation erodes that authority, the adaptive law may misinterpret tracking errors, leading to parameter drift, performance loss, or instability. To overcome these limitations, the proposed framework embeds human supervisory judgment directly into the control loop, detecting subtle off-nominal behavior, validating or overriding controller parameters, and adjusting operational objectives when conditions exceed the modeled fault space. Two new metrics underpin this resilient decision-making: Generation Reserve Capacity (GRC), which quantifies remaining inverter capacity available for future contingencies, and Controlled Performance Degradation (CPD), which allows temporary, deliberate performance relaxation to preserve overall system operability. A human-selected resilience tuning parameter, μ, governs the trade-off between immediate tracking accuracy and long-term operational readiness. A stability analysis of the proposed HOTL μ-mod adaptive controller is presented. The approach is also validated through simulations of a grid-connected inverter under sequential actuator degradation. Results show that the proposed architecture preserves control reserves, prevents actuator saturation, and achieves superior voltage regulation compared with conventional adaptive control and FTC methods.
