Article
Sturdy Model Predictive Control for Satellite Attitude Control System Using MRAS
The author proposes an enhanced robust model predictive controller (RMPC) which is founded on a model reference adaptive system (MRAS). The MRAS technique allows building a RMPC controller using combinational methods for three-degree-of-freedom satellites that handles external disturbances and moment of inertia uncertainty to preserve the stability and performance of the closed-loop system. The derivation of the state feedback control rule requires solving a convex optimization problem subject to multiple linear matrix inequalities (LMIs). An Input constraint functions as an LMI within the mentioned optimization framework to protect actuator saturation. Through the MRAS method all disturbances present in the system input become obsolete. By implementing this algorithm operators gain several advantages because it maintains stability under uncertain model conditions while collecting exact system information. The proposed method delivers system simulation results which demonstrate improvements compared to those obtained from generalized Incremental Model Predictive Control (GIPC). The suggestive controller achieves superior robustness when compared to the GIPC approach according to the experimental results.
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