Delta机器人增广非线性PD控制研究

Research on Augmented Nonlinear PD Control for Delta Robot

针对Delta机器人高速运动时的精度控制问题,基于虚功原理和从动臂集中质量方法建立机器人动力学模型,有效地提高了模型求解效率。在此基础上,结合逆动力学模型进行力矩前馈补偿,并引入非线性饱和函数代替传统定常控制参数,实现对Delta机器人的增广非线性PD控制。为了验证该算法的控制效果,联合ADAMS与Simulink软件建立机器人虚拟样机,同时在自研的机器人实物样机上搭建运动控制试验平台。仿真和试验结果表明:跟增广PD控制相比,增广非线性PD控制能获得更高的控制精度,且高速运动时精度提升更为明显。

Aiming at the high-velocity motion control problem of Delta robot,based on virtual work principle and centralized mass model of forearms,a dynamic model is established,which effectively improves the efficiency of model solving.On this basis,the torque feedforward compensated by using this inverse dynamic model,and a non-linear saturation function is introduced to replace the traditional steady control parameters to achieve an augmented nonlinear PD control for the Delta robot.In order to verify the control effect of this algorithm,a virtual prototype was established in conjunction with ADAMS and Simulink software,and a test platform was built on a self-developed Delta robot.Simulation and experiment results show that the augmented nonlinear PD control can obtain higher control accuracy than the augmented PD control,and the improvement of control precision is more obvious in high speed.