Flourence and Kin Chie 02 06 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 threedegreeoffreedom satellites that handles external disturbances and moment of inertia uncertainty to preserve the stability and performance of the closedloop 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 Copyright (c) Journal of Science Engineering Technology and Management Science. All rights reserved 2026