This study focuses on enhancing the control precision and efficiency of a two-degree-of-freedom (2-DOF) space manipulator used for active space debris removal. The unpredictable space environment introduces large uncertainties, which introduces unique challenges beyond the capabilities of a standalone computed torque controller and degrades control performance. To address this problem, a robust controller is developed, integrating traditional techniques such as sliding mode and computed torque control with a Neural Network framework. This synergy leverages both methods' strengths—conventional controls' accuracy and Neural Network's adaptability. The integration of Neural Network-based sliding mode control complements the robustness of computed torque control by actively mitigating uncertainties and disturbances inherent in the space environment. The 2-DOF manipulator's state variables model the system dynamics, necessitating accurate relative motion estimation between the manipulator and debris. The global asymptotic stability of the developed algorithm is demonstrated through the Lyapunov theorem, guaranteeing error convergence to zero. The convergence, stability, precision, tracking errors, and responsiveness of the controller have been analysed and validated by the MATLAB Simulink simulations. The novel approach's performance effectiveness is substantiated by numerical simulations and a comparative analysis with conventional computed torque control. Outcomes highlight the superior precision and efficiency in manipulator tracking the trajectory, validating the integrated controller's potential for successful active space debris removal.

中文翻译：

---

空间机械手的智能和鲁棒控制，可持续清除空间碎片

本研究的重点是提高用于主动空间碎片清除的二自由度（2-DOF）空间机械臂的控制精度和效率。不可预测的空间环境带来了很大的不确定性，这带来了超出独立计算扭矩控制器能力的独特挑战，并降低了控制性能。为了解决这个问题，开发了一种鲁棒控制器，将滑模和计算扭矩控制等传统技术与神经网络框架相集成。这种协同作用利用了两种方法的优势——传统控制的准确性和神经网络的适应性。基于神经网络的滑模控制的集成通过主动减轻空间环境中固有的不确定性和干扰来补充计算扭矩控制的鲁棒性。 2-DOF 机械臂的状态变量对系统动力学进行建模，需要对机械臂和碎片之间进行准确的相对运动估计。通过李亚普诺夫定理证明了所开发算法的全局渐近稳定性，保证误差收敛为零。控制器的收敛性、稳定性、精度、跟踪误差和响应能力已通过 MATLAB Simulink 仿真进行了分析和验证。该新方法的性能有效性通过数值模拟以及与传统计算扭矩控制的比较分析得到证实。结果凸显了机械臂跟踪轨迹的卓越精度和效率，验证了集成控制器成功主动清除空间碎片的潜力。