摘要
针对非线性机器人系统的轨迹跟踪问题,提出一种终端滑模重复学习混合控制方案.该方案综合了重复学习控制和终端滑模技术的特性,能够有效跟踪周期性参考信号,抑制周期性和非周期性动态的干扰,具有较强的鲁棒性和良好的轨迹跟踪性能,且算法的实现不需要完全已知系统模型信息.应用Lyapunov稳定性理论证明了闭环系统的全局渐近稳定性.三自由度机器人系统数值仿真结果验证了所提出的终端滑模重复学习控制的有效性.
In order to make a robot precisely track desired periodic trajectories, a terminal sliding mode based repetitive learning control method is proposed, which incorporates characteristics of terminal sliding mode control into repetitive learning control. The hybrid control schemes utilize learning-based feedforward terms to compensate for periodic dynamics and terminal sliding mode-based feedback terms to compensate for nonperiodie dynamics. Advantages of the proposed control include the absence of model parameter in the control law formulation and improved robustness and tracking performance compared with the conventional approaches. The Lyapunov＇s direct method is employed to prove global asymptotic tracking. Simulation results on a three degree-of-freedom（DOF） robot illustrate the effectiveness of the proposed scheme.
出处
《控制与决策》
EI
CSCD
北大核心
2014年第7期1291-1296,共6页
Control and Decision
关键词
机器人控制
轨迹跟踪
重复学习控制
终端滑模
全局渐近稳定性
robot control
tracking
repetitive learningcontrol
terminal sliding mode
global asymptotic stability
