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Adaptive controller design for spacecraft formation flying using sliding mode controller and neural networks. (English) Zbl 1254.93085
Summary: A spacecraft formation flying controller is designed using a sliding mode control scheme with the adaptive gain and neural networks. Six-degree-of-freedom spacecraft nonlinear dynamic model is considered, and a leader–follower approach is adopted for efficient spacecraft formation flying. Uncertainties and external disturbances have effects on controlling the relative position and attitude of the spacecrafts in the formation. The main benefit of the sliding mode control is the robust stability of the closed-loop system. To improve the performance of the sliding mode control, an adaptive controller based on neural networks is used to compensate for the effects of the modeling error, external disturbance, and nonlinearities. The stability analysis of the closed-loop system is performed using the Lyapunov stability theorem. A spacecraft model with 12 thrusts as actuators is considered for controlling the relative position and attitude of the follower spacecraft. Numerical simulation results are presented to show the effectiveness of the proposed controller.
93C40Adaptive control systems
93B12Variable structure systems
93A14Decentralized systems
92B20General theory of neural networks (mathematical biology)
93D09Robust stability of control systems
93D05Lyapunov and other classical stabilities of control systems
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