Nonlinear Momentum Transfer Control by Using Neural Networks

A nonlinear control law design for the momentum transfer of spacecraft with a single momentum wheel is addressed. The spacecraft model contains a momentum wheel and a spring-mass-damper system as internal dynamics. The proposed control law for the momentum transfer is based upon the feedback linearization technique in combination with a neural network to account for uncertainties in modelling the internal dynamics. A reference trajectory is pre-dened to lead to a smoothed tracking control torque prole. The output function is dened as a component of the angular momentum vector for the successful transfer maneuver. For feedback lienarization which usually requires exact system model, the neural network is employed for model error compensation. Stability of the control law including adaptation using the neural network is proved by the Lyapunov stability theory.

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