Novel finite-time adaptive neural control of flexible spacecraft with actuator constraints and prescribed attitude tracking performance

Abstract

A novel finite-time neural control strategy is proposed for flexible spacecraft with guaranteed attitude tracking performance subject to parametric uncertainty, uncertain external disturbance, unmeasured elastic vibration and actuator saturation. First, a new finite-time performance function is developed. Then, unlike some existing prescribed performance control methodologies, a novel finite-time controller is derived to guarantee that the attitude tracking errors can converge to a preselected range of the equilibrium within predetermined time independent of the initial conditions. The derived controller is then extended by a neural network compensator to reject the disturbance and overcome the unknown actuator saturation. Specially, the computation burden is reduced by updating the norm of ideal weight vectors rather than their elements with the aid of minimal-learning-parameter technique. Finally, apart from showing the stability of the closed-loop system, numerical simulations demonstrate the effectiveness, robustness and superiority of the proposed approach.