An adaptable control system within and on-board a network of interacting satellites is an important module which is desired for unmanned space vehicles. However, such a control system is not easy to develop since it is the core of the network’s operation and all the earth-linked operational information is reviewed and analyzed through it. Due to multipurpose missions of satellites, several decisions are made simultaneously about necessary changes to the satellite’s operational parameters (i.e., orbit, inclination, etc.). In this paper, a neural network model-based control scheme is developed for a network of interacting satellites. The proposed neural control scheme refers to a methodology in which the controller is assumed as a neural network and the dynamical model of the system is identified through the training stages of the neural model. The simulation results show that the neural control method can be effectively applied in monitoring and controlling the satellite networks, without the necessity of determining the mathematical model of the system.

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