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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
引用本文:姜春福,余跃庆. 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[J]. 机械传动, 2003, 27(1): 6-10
作者姓名:姜春福  余跃庆
作者单位:北京工业大学机电学院,北京,100022
摘    要: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。

关 键 词:神经网络 参数自整定 PID控制 协调操作 轨迹跟踪 轨迹控制 工业机器人
文章编号:1004-2539(2003)01-0006-05

Trajectory Tracking Control of Two Cooperative Manipulators Through the Combination of Neural Network and PID Controller
Jiang Chunfu,et al.. Trajectory Tracking Control of Two Cooperative Manipulators Through the Combination of Neural Network and PID Controller[J]. Journal of Mechanical Transmission, 2003, 27(1): 6-10
Authors:Jiang Chunfu  et al.
Abstract: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.
Keywords:Cooperative Manipulators Neural Network PID Control  
本文献已被 CNKI 维普 万方数据 等数据库收录!
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