基于神经网络参数自整定PID的双臂机器人协调操作的轨迹跟踪控制

Trajectory tracking control of Two Cooperative Manipulators Through the Combination of Neural Network and PID Controller

将BP神经网络与PID相结合 ,解决了双臂机器人协调操作同一刚性负载的轨迹控制问题 ,设计了应用于机器人协调操作刚性负载轨迹跟踪的控制系统。针对主臂和从臂在实际操作中所处地位的不同 ,对主臂、从臂应用了不同的控制子结构。采用这一方法 ,可以实时调整PID控制器的参数 ,使其在线达到最优状态 ,克服了依靠经验离线整定PID参数的局限 ,使系统具有更强的鲁棒性和自适应性 ,其输出可达到期望的控制精度。仿真实验验证了控制系统及算法的有效性。

A method of combining BP neural network with PID controller is applied to two manipulators cooperating a rigid payload. Based on kinetic constraints of two robots manipulating one rigid object, different control subsystems are designed for the leader and follower according to the roles they play in the system. PID parameters can be rectified online in the two subsystems, which makes the parameters achieve optimized values. With the optimized parameters, the control system can be more robust and more adaptive. The validity of the adoption was verified by numerical simulation.