Robust tracking control of space robots with prescribed performance
This paper investigates the robust tracking control of space robots under prescribed performance constraints.We convert the original tracking problem into the boundedness control of mapping errors via the bidirectional unconstrained mapping approach by incorporating a prescribed performance function with fixed-time convergence property.Furthermore,the reference acceleration is designed based on the reduced-order method,and the uncertainty of the system is compensated by the neural network to achieve robust tracking of the time-varying desired trajectory,ensuring that the mapping error is always bounded and the tracking error meets the prescribed performance indicators of convergence within the specified time.The numerical simulation results verify the effectiveness of the proposed method.
space applicationsuncertain systemsprescribed performancerobust tracking
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