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非线性时滞大系统自适应神经网络分散控制 被引量：13

Adaptive Neural Network Decentralized Control for Nonlinear Time-delay Large-scale Systems
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摘要 针对一类未知非线性时滞关联大系统,提出一种自适应神经网络分散跟踪控制方案.采用神经网络逼近各子系统内部的非线性函数和关联项中的时滞非线性函数;利用占有方法处理时滞项,采用B ackstepp ing技术设计分散控制律和参数自适应律.基于Lyapunov-K rasov isk ii泛函证明了闭环大系统所有信号半全局一致最终有界.通过调节设计参数和增加神经元个数,可以实现任意输出跟踪精度.实例仿真说明了该方案的可行性. A decentralized adaptive neural network （NN） tracking control approach is presented for a class of unknown large-scale nonlinear time-delay systems. Both the delay-independent functions of subsystems and the delay-dependent functions of interconnections are approximated by NNs. Domination method is used to deal with the time-delay terms. The decentralized control laws and the parameter adaptive laws are designed by Backstepping techique. Based on Lyapunov-Krasoviskii functional, the semi-global uniform ultimate boundedness （SGUUB） of all signals in the closed-loop system is proved. The arbitrary output tracking accuracy is achieved by tuning the design parameters and increasing the neural node number. An illustrative simulation example shows the feasibility.
作者 陈为胜 李俊民
机构地区 西安电子科技大学应用数学系
出处 《控制与决策》 EI CSCD 北大核心 2006年第8期873-878,共6页 Control and Decision
基金 国家自然科学基金项目(60374015) 陕西省自然科学基金项目(2003A15)
关键词 时滞大系统 神经网络 分散控制 BACKSTEPPING Delayed large-scale systems Neural network Decentralized control Backstepping
分类号 TP13 [自动化与计算机技术—控制理论与控制工程]
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参考文献11

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共引文献14

同被引文献79

引证文献13

二级引证文献17

控制与决策
2006年 第8期

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