| 引用本文: | 罗隆,罗飞,许玉格.不确定非线性系统全局渐近自适应神经网络控制[J].控制理论与应用,2014,31(9):1268~1273.[点击复制] |
| LUO Long,LUO Fei,XU Yu-ge.Global asymptotic adaptive neural control of uncertain nonlinear systems[J].Control Theory and Technology,2014,31(9):1268~1273.[点击复制] |
|
| 不确定非线性系统全局渐近自适应神经网络控制 |
| Global asymptotic adaptive neural control of uncertain nonlinear systems |
| 摘要点击 2223 全文点击 1927 投稿时间：2013-12-23 修订日期：2014-04-07 |
| 查看全文 查看/发表评论 下载PDF阅读器 |
| DOI编号 10.7641/CTA.2014.31361 |
| 2014,31(9):1268-1273 |
| 中文关键词 自适应控制 渐近跟踪 神经网络 全局稳定 非线性系统 |
| 英文关键词 adaptive control asymptotic tracking neural network global stability nonlinear system |
| 基金项目 中央高校基本科研业务费专项重点资助项目(2014ZZ0037); 广州市珠江科技新星项目(2011J2200084); 广州市“节能减排(水处理)自动 化技术应用研究创新学术团队”项目(穗教科2009[11]号); 惠州市产学研结合项目(2011C010002004). |
|
| 中文摘要 |
| 针对一类控制增益为一般函数形式的不确定仿射非线性系统, 提出一种能够确保全局渐近稳定的自适应 神经控制(adaptive neural control, ANC)方法. 为了保证神经网络逼近的适用性, 设计一种可变控增益的比例微 分(proportional differential, PD)控制器以全局镇定被控对象. 利用状态变换解决由未知控制增益函数导致的控制奇 异问题. 提出一种连续的自适应鲁棒控制项实现闭环系统的渐近跟踪. 与现有的全局渐近跟踪ANC方法相比较, 本 文方法不仅简化了PD增益的选择, 而且减轻了控制输入的颤振问题. 仿真结果表明了本文方法的有效性. |
| 英文摘要 |
| We present an adaptive neural control (ANC) strategy that guarantees globally asymptotic tracking for a class of uncertain nonlinear systems with function-type control gains. A proportion differential (PD) control term with variable gain is employed to globally stabilize the plant so that neural network approximation is applicable. A state transformation is applied to solve the control singularity problem resulting from the unknown control gain function. A robust control term is developed to achieve asymptotic tracking of the closed-loop system. Compared with previous global asymptotic tracking ANC approaches, the proposed approach not only simplifies the selection of PD gain, but also relaxes chattering at the control input. Simulation results have demonstrated the effectiveness of the proposed approach. |