混联机械臂系统自适应选择迭代学习角同步控制

ADAPTIVE SWITCHING ITERATIVE LEARNING ANGLE SYNCHRONOUS CONTROL FOR HYBRID MANIPULATOR SYSTEM

建立了四自由度混联机械臂系统动力学模型,并根据系统重复运动和具有不确定因素的特点,设计了自适应选择迭代学习同步控制算法(ASILSC),实现了系统的角同步运动,并证明控制算法的收敛性。仿真结果表明,相比于带遗忘因子的迭代学习同步控制,自适应选择迭代学习角同步控制有更好的收敛性和鲁棒性。

The dynamic model of the four-degree-of-freedom hybrid manipulator system was established.According to the characteristics of the system’s repeated motion and uncertain factors,the adaptive switching iterative learning angle synchronous control(ASILSC)was designed to achieve the angular synchronization of the system.The convergence of the control algorithm was proved.The simulation results showed that compared with the iterative learning synchronization control method with forgetting factor,the iterative learning synchronous control method based on adaptive switching had better convergence and robustness.