空间机器人捕获目标后双幂次滑模神经网络补偿控制
发布时间：2018-08-07 19:04
【摘要】：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。
[Abstract]:In this paper, the impact effect of collision and the problem of stability control are studied when the space robot system catches the target with uncertain parameters. The dynamic model of space robot and target is obtained by using the theory of multi-rigid body system. Based on the kinematic geometry and the force transfer relationship between the end of the manipulator and the target, the impact of the target captured by the space manipulator is analyzed. In view of the uncertainty of the parameters and the external disturbance of the system after the acquisition operation, a double-power sliding mode neural network scheme is proposed. The convergence rate of the system is guaranteed by using the fast double power sliding mode approach law. The neural network is used to approximate the parameter uncertainty and the external disturbance of the system. The above control scheme has the effect of suppressing buffeting. Based on Lyapunov method, a weighted adaptive law is designed, and the global stability of the system is proved. The impact effect is simulated by computer numerical simulation, and the effectiveness of the control scheme is verified.
【作者单位】： 福州大学机械工程及自动化学院福建省高端装备制造协同创新中心;
【基金】：国家自然科学基金(11372073,11072061) 福建省工业机器人基础部件技术重大研发平台(2014H21010011)
【分类号】：TP183;TP242
，
本文编号：2171057
[Abstract]:In this paper, the impact effect of collision and the problem of stability control are studied when the space robot system catches the target with uncertain parameters. The dynamic model of space robot and target is obtained by using the theory of multi-rigid body system. Based on the kinematic geometry and the force transfer relationship between the end of the manipulator and the target, the impact of the target captured by the space manipulator is analyzed. In view of the uncertainty of the parameters and the external disturbance of the system after the acquisition operation, a double-power sliding mode neural network scheme is proposed. The convergence rate of the system is guaranteed by using the fast double power sliding mode approach law. The neural network is used to approximate the parameter uncertainty and the external disturbance of the system. The above control scheme has the effect of suppressing buffeting. Based on Lyapunov method, a weighted adaptive law is designed, and the global stability of the system is proved. The impact effect is simulated by computer numerical simulation, and the effectiveness of the control scheme is verified.
【作者单位】： 福州大学机械工程及自动化学院福建省高端装备制造协同创新中心;
【基金】：国家自然科学基金(11372073,11072061) 福建省工业机器人基础部件技术重大研发平台(2014H21010011)
【分类号】：TP183;TP242
，
本文编号：2171057
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