Human-on-the-loop Resilient Control of InverterBased Resources Under Actuator Degradation

Majid Dehghani, Taha Saeed Khan, Hamidreza Nazaripouya

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.