空间机器人捕获目标后双幂次滑模神经网络补偿控制

Two Power Sliding Mode Neural Network Compensation Control for Space Robot after Target Capturing

研究了空间机器人系统捕获不确定参数目标时发生碰撞的冲击效应及之后的稳定控制问题。利用多刚体系统理论获得空间机器人及目标动力学模型。利用运动几何关系及机械臂末端与目标物之间力的传递关系,分析了空间机械臂捕获目标的冲击影响。针对完成捕获操作后的联合体系统存在参数不确定及外部扰动的情况,提出了双幂次滑模神经网络方案。利用快速双幂次滑模趋近律保证了系统的收敛速度,运用神经网络逼近系统的参数不确定项及外部扰动,上述控制方案具有抑制抖振的效果。基于李雅普诺夫方法,设计了权值自适应律,证明了系统的全局稳定性。计算机数值仿真实验模拟了碰撞冲击效应,验证了上述控制方案的有效性。

The impact analyses of space robot capturing a target and stability control problem in the post-impact process were discussed. The dynamic models of space robot system and target were derived by multi-body theory. The impact effect of rigidcouplingmodel was analyzed by applying geometric relationship and principle of momentum conservation. Atwo power sliding mode neural network control scheme was proposed for the combined system after acquiring with uncertain system parameters and external disturbance. The convergence speed of the control system was guaranteed by applyingtwo power sliding mode reaching raw, and the uncertain part was compensated by using neural network. The proposed control scheme can eliminate the chattering. Based on the Lyapunov method, the weights adaptive law was designed and the stability of the combined system was demonstrated. Computer numerical simulation example simulated the process of collision impact effect and verified the validity of the proposed control scheme.