كنترل مود لغزشي هوشمند ماهواره انعطاف پذير در حالت كمبود عملگر

Abstract In this research, the design an‎d analysis of robust control strategies for flexible satellites under actuator shortage conditions are investigated. Although flexible satellites benefit from advantages in terms of mass an‎d cost, they face challenges such as unwanted vibrations an‎d instability, which become more severe under actuator deficiency an‎d make achieving full attitude control difficult. To address this issue, super-twisting control an‎d higher-order adaptive sliding mode control are employed, both integrated with reinforcement learning for automatic tuning of control gains. This combination aims to maintain stability, reduce control chattering, an‎d improve tracking accuracy. The dynamic modeling of the system is carried out using Lagrangian mechanics, an‎d the effects of environmental disturbances an‎d actuator failures on system dynamics are analyzed. The objectives of this study are defined as developing two robust sliding mode–based controllers adapted to actuator shortage an‎d model uncertainties, integrating each with reinforcement learning for adaptive gain tuning, an‎d eva‎luating the performance of the proposed strategies in terms of tracking accuracy, vibration damping, an‎d chattering reduction across various operational scenarios. Simulation results demonstrate that the proposed hybrid approach significantly enhances stability an‎d accuracy compared with conventional methods, reduces the system’s sensitivity to disturbances an‎d actuator failures, an‎d thus confirms the effectiveness of robust an‎d intelligent control methods in extending operational lifetime an‎d improving the performance of flexible satellites.

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