Monte-Carlo Based Optimal Control Strategy Through State Estimator in Autonomous Space Systems

Amir Hooshang Mazinan


The present research relies on a control strategy to deal with the dynamics and its kinematics of the space systems, while a band of parameters uncertainties and disturbances in line with the variations of the thrust vector, center of mass, engine misalignment, moments of inertial and so on are taken into real consideration. To present the investigated outcomes in such a real situation, the process noise that are related to a set of thrusters and the measurement noise that are also related to a set of sensors are considered to be dealt with through optimal state estimator scheme. There are the double control loops including the inner loop and the outer loop, which are organized based upon a combination of low and high thrusts levels to handle three-axis rotational angles and its rates. The aforementioned thrusts levels in connection with the uncertainties and disturbances are handled through the Monte-Carlo based method to consider the proposed approach performance in a series of experiments. The acquired investigated results indicate that the performance of the proposed strategy is verified in which the well-known state-dependent Riccati equation based on the three-axis rotational angles and the corresponding angular rates is considered as the benchmark approach to be compared in the same conditions.



Monte-Carlo based method, comprehensive control strategy, optimal estimator, a band of uncertainties, disturbances.

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Print ISSN: 1392-124X 
Online ISSN: 2335-884X