基于FCMAC的鲁棒自适应迭代学习控制算法  

FCMAC-Based Robust Adaptive Iterative Learning Control Algorithm

作　　者：孙开林[1] 王宪[1] 杨坤[1] 

机构地区：[1]江南大学物联网工程学院,无锡214122

出　　处：《计算机系统应用》2011年第11期86-90,共5页Computer Systems & Applications

摘　　要：工业机器人在改变运动轨迹时往往伴随着系统噪声、干扰的引入以及自身的惯量参数发生变化,采用传统的迭代控制算法难以达到高精度、高速控制的要求。将自适应与鲁棒控制与迭代控制相结合,提高迭代算法的控制精度;给定任务发生改变时,引入模糊小脑关节控制器作为前馈控制,经历史控制经验训练后估算出变化后系统的期望估计输入,作为迭代控制器的初始输入,避免了在新任务产生时盲目的选择初始量,达到高速控制目的。对机器人系统的仿真结果验证了本算法的有效性和合理性。Trajectory Changing of the industrial robots are often accompanied by system noise, interference, and the introduction of its own inertia parameters change, and the traditional iterative control algorithm is difficult to achieve high precision and high-speed control requirements. This article combines adaptive control and robust control and the iterative algorithm together to improve the control precision; when the given task is changed, the historical control experience estimates the changes in training estimated input after the system＇s expectations, as the initial iteration controller input, the controller works as joint fuzzy cerebellar feed-forward control, when new tasks arise it avoids the choice of the initial amount of the blind in the order to achieve high-speed control purposes. At last the robot system simulation results show the validity and rationality of the algorithm.

关 键 词：FCMAC 迭代学习控制 鲁棒自适应 

分 类 号：TP13[自动化与计算机技术—控制理论与控制工程] TP242[自动化与计算机技术—控制科学与工程]