A Controller Design for Approaching Disabled Satellites Based on Discrete Sample Points

When approaching and removing a disabled satellite, the accuracy of the controller is imperative to the success of the mission because if the mission fails, more space debris can be produced due to satellite collision. To address this issue, a controller directly driven by discrete sample data points is proposed in this paper. First, the input vector for the controller is placed into a state space as a point. The state space also contains points constructed by the input vectors of pre-generated samples, which are created by the GPOPS planning algorithm along with control commands as sample output vectors. Then, an adjacent range is selected and the sample points within are collected. To accelerate the process, a series of data processing methods are implemented, including the dichotomy method, table look-up method, and random selection method. Finally, the control commands are computed using the iteratively reweighted least-squares algorithm with the assumption that similar inputs have similar outputs. According to the simulation results, the discrete point controller is more precise than the neural network controller.