摘要
对于一个未知的非线性连续系统或离散系统,从任给的一个初始控制出发,尝试实现一条给定的输出目标轨线。在满足一定条件下,利用跟踪误差来修正控制函数,经过反复的迭代学习可以取得满意的效果。本文改进了Arimoto、Togai和Bien等的开环迭代学习的收敛条件,并提出闭环迭代学习算法。理论与仿真结果证明了闭环算法在收敛条件、速度和抗干扰能力上都优于开环算法。
A simple iterative learning algorithm could be used to control the nonlinear dynamical systems by updating the control function from an arbitrary initial trial. This paper improves the convergent condition on the open loop iterative learning schemes posed by Arimoto, M.Togai,Z. Bien, et al., and develops a closed-loop version. It is proved theoretically and demonstrated via simulations that the closed-loop learning scheme is superior to the previous strategies in convergent condition, learning speed and disturbance rejection.
出处
《自动化学报》
EI
CSCD
北大核心
1992年第2期168-176,共9页
Acta Automatica Sinica
基金
国家科学基金No.68974016
关键词
机械手
非线性系统
学习算法
Nonlinear system
iterative control
learning algorithm
intelligent control.
