Volume 60

SAC-Optimized Active Disturbance Rejection Controller for Thermal Regulationin Aerospace Applications Dong Li, Yanping Gu, Li Sun

Abstract

Efficient temperature regulation is essential formaintaining the sensitivity and noise performance ofspaceborne infrared detectors under varyingobservation modes. This paper proposes an ActiveDisturbance Rejection Controller (ADRC) with dynamicparameter tuning based on the Soft Actor-Critic (SAC)reinforcement learning algorithm, aiming to optimize thetemperature control performance and disturbancerejection capability of spacecraft systems. A thermaltransfer model was established, and the Soft Actor-Critic(SAC) algorithm was introduced to dynamically tuneparameters (system gain, controller bandwidth andobserver bandwidth) by maximizing a weighted sum ofthe reward and policy entropy. This approach enablesreal-time estimation and compensation of totaldisturbances. Simulation results demonstrate that, intemperature tracking tasks, the proposed methodreduces the integral of absolute error (IAE) by 14.61%and 14.87%, and shortens the settling time by 36.36%and 58.47%, compared to fixed-parameter ADRC and PIDcontrollers, respectively. Under external periodicdisturbances, the proposed controller improves controlaccuracy by 15.6% and 13.6%. Monte Carlo robustnesstests further show that, under ±5% parameterperturbations, the method exhibits small fluctuations inIAE, settling time, and overshoot. The proposed SAC-ADRC strategy provides a promising solution for rapidand high-precision thermal regulation of infrareddetectors in aerospace applications.

Keywords Aerospace thermal control, High-PrecisionTemperature Control, Active Disturbance RejectionController (ADRC), Soft Actor-Critic (SAC), Infrareddetector