混合驱动柔索并联机器人自适应迭代学习控制

Adaptive Iterative Learning Control of Hybrid Drive Cable Parallel Manipulator

以一种兼容混合驱动机构与柔索并联机构特点的新型混合驱动柔索并联机器人为研究对象,对其动力学建模及轨迹跟踪控制进行了研究;应用Lagrange方法建立了混合驱动柔索并联机器人系统的动力学模型;针对具有非线性、时变特性以及带有可重复时变干扰的混合驱动柔索并联机器人动态系统模型,设计了一种控制增益随迭代次数变化的自适应迭代学习控制策略,并采用Lyapunov函数证明了该控制器的稳定性;数值仿真结果表明,在该控制器的作用下,混合驱动柔索并联机器人控制系统能够完成高精度跟踪期望轨迹,进一步验证了所建系统动态模型的正确性及控制策略的有效性。

Dynamics modeling and trajectory tracking control of a novel hybrid drive cable parallel manipulator(HDCPM)which has the advantages of both cable parallel mechanism and hybrid drive mechanism are investigated.A dynamics model for a HDCPM is established by using Lagrange method.For a HDCPM system with nonlinear,time-varying characteristics and repetitive time-varying disturbance,an adaptive iterative learning control strategy,which controls gain variations with the iterations,is designed.By means of Lyapunvo function,the stability of the controller is proved.The numerical simulation results indicate that an expect trajectory tracking of the HDCPM is achieved by the adaptive iterative learning controller,which illustrates the correctness of the built dynamic model and the validity of proposed control strategy.