空间机器人预设性能约束下的鲁棒跟踪控制

This paper investigates the robust tracking control of space robots under prescribed performance constraints. By incorporating a predefined performance function with specified time convergence and a bidirectional unconstrained mapping, we convert the tracking problem of space robots into a boundedness control problem of mapping errors. 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. The proposed method ensures 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.