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基于神经网络的非线性系统轨迹线性化自适应容错控制 被引量：1

Adaptive fault-tolerant control of nonlinear systems using trajectory linearization based on neural network
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摘要 针对一类仿射非线性系统,首先采用轨迹线性化方法将其等价表示为线性时变系统;然后利用神经网络构建伪逆模型以及动态故障模型;最后基于模型参数变化,应用李亚普诺夫稳定性理论构建标称系统控制器及故障补偿控制律,从而实现系统故障下的稳定有界容错控制.仿真结果表明了所提出算法的有效性. Aiming at a class of affine nonlinear system, a trajectory linearization method is used to equivalently transform the nonlinear system into a linear time-varying（LTV） system. Then, a pseudo-inverse and a fault dynamic model are established by using neural network. Finally, the nominal controller and the fault accommodation laws are established by using the Lyapunov method from parameter variety. Thus the stability of the fault-suffered system is ensured. Simulation results show the effectiveness of the proposed algorithm.
作者 赵峻 孙伟 王雪松
机构地区 中国矿业大学信息与电气工程学院
出处 《控制与决策》 EI CSCD 北大核心 2011年第6期902-906,共5页 Control and Decision
基金 国家自然科学基金项目(60804022)
关键词 轨迹线性化 非线性 伪逆模型 自适应 容错控制 trajectory lineadzatiom nonlinear pseudo-inversemodel adaptive, fault-tolerant control
分类号 TP273 [自动化与计算机技术—检测技术与自动化装置]
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参考文献11

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二级参考文献11

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共引文献3

同被引文献12

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控制与决策
2011年 第6期

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