.png){kind=icon}
返回
Robust intelligent tracking control with PID-type learning algorithm
.png){kind=icon}
PRE
AI
DOI：10.1016/j.neucom.2007.01.002.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This paper proposes a robust intelligent tracking controller (RITC) for a class of unknown nonlinear systems. The proposed RITC system is comprised of a neural controller and a robust controller. The neural controller is designed to approximate an ideal controller using a proportional-integral-derivative (PID)-type learning algorithm in the sense of Lyapunov function, and the robust controller is designed to achieve L-2 tracking performance with desired attenuation level. Finally, to investigate the effectiveness of the RITC system, the proposed design methodology is applied to control two chaotic dynamical systems. The simulation results verify that the proposed RITC system using PID-type learning algorithm can achieve faster convergence of the tracking error and controller parameters than that using I-type learning algorithm. (c) 2007 Elsevier B.V. All rights reserved.
Keyword:
adaptive control
neural network control
robust control
Lyapunov function
chaotic dynamic system
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
6.5
论文数:
2.5W
被引数:
6.5W
机构
暂无机构信息
引用论文
.png){kind=icon}
Development of intelligent position control system using optimal design technique利用优化设计技术开发智能位置控制系统
PREAI
分享收藏Fertilizer sowing simulation of a variable-rate fertilizer applicator based on EDEM基于EDEM的变量施肥机播种模拟
OAAI
OAAI分享收藏
查看更多内容