引用本文: | 解学军,王远.基于神经元网和带死区的最小二乘算法的非线性离散时间系统的自适应控制[J].控制理论与应用,1999,16(3):355~360.[点击复制] |
Xie Xuejun and Wang Yuan.Adaptive Control of Nonlinear Discrete-Time Systems Using Neural Networks and Least Squares Algorithm with Dead-Zone[J].Control Theory and Technology,1999,16(3):355~360.[点击复制] |
|
基于神经元网和带死区的最小二乘算法的非线性离散时间系统的自适应控制 |
Adaptive Control of Nonlinear Discrete-Time Systems Using Neural Networks and Least Squares Algorithm with Dead-Zone |
摘要点击 1273 全文点击 558 投稿时间:1998-03-02 修订日期:1998-09-09 |
查看全文 查看/发表评论 下载PDF阅读器 |
DOI编号 |
1999,16(3):355-360 |
中文关键词 非线性系统 多层神经元网 带死区的最小二乘算法 自适应控制 |
英文关键词 Nonlinear systems multilayer neural networks least squares algorithm with dead-zone adaptive control |
基金项目 |
|
中文摘要 |
针对非线性离散时间系统,提出了一种用带死区的最小二乘算法去调节神经网参数的算法,同其他算法相比,这种算法具有非常高的收敛速度,对于这种自适应控制算法,证明了闭环系统的所有信号是有界的,跟踪误差收敛到以零为原点的球中。 |
英文摘要 |
Multilayer neural networks are used in a nonlinear discrete0time adaptive control problem. The weights of the neural networks are uqdated by using least squares (LS) algorithm with dead-zone. LS algorithm has much superior rate of convergence compared with gradient algorithm and δ-modification algorithm. For the adaptive control algorithm, we prove that: 1) all signals in the closed-loop systems are bounded; and 2) the tracking error converges to a bounded ball. |