基于UIO的减摇鳍控制系统故障诊断算法
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(哈尔滨工程大学 自动化学院, 150001 哈尔滨)

作者简介:

孙蓉(1978—),女,博士,讲师; 刘胜(1957—),男,教授,博士生导师.

通讯作者:

李冰,libing265@hrbeu.edu.cn.

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基金项目:

国家自然科学基金资助项目(51079033);中央高校基本科研业务费项目资助(HEUCF041229,HEUCF041205,HEUCFX41305).


Fault diagnosis algorithm for fin stabilizer control system based on unknown input observer
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(College of Automation,Harbin Engineering University,150001 Harbin,China)

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    摘要:

    为提高减摇鳍控制系统可靠性,提出了基于UIO的减摇鳍控制系统故障诊断算法,改进了基于全阶Luenberger故障诊断观测器针对系统出现未知扰动时的不足.利用最优解耦原理,设计了满足系统出现未知扰动时可解耦的UIO故障诊断观测器,推导及证明了减摇鳍控制系统存在UIO的充要条件,并给出了UIO故障诊断观测器的设计步骤.以NJ5型减摇鳍控制系统为研究对象,验证算法的有效性.仿真结果表明,基于UIO的减摇鳍控制系统故障诊断算法相比传统方法,获得的状态估计误差小,且收敛速度快;在故障诊断阶段,有效提高了残差的收敛效果,并对系统出现的故障作出快速响应.

    Abstract:

    To improve the reliability of fin stabilizer control system, a fault diagnosis algorithm for the fin stabilizer control system based on UIO is presented. The algorithm improves the deficiency compared with the full order Luenberger fault diagnosis observer when the unknown disturbance occurs in the system. Using the optimal decoupling principle, the UIO fault diagnosis observer which can be decoupled to the unknown disturbances is designed. The existence of the UIO necessary and sufficient condition is deduced and proved for the fin stabilizer control system, and then the UIO fault diagnosis observer design steps are listed. The validity of the algorithm based on the NJ5 fin stabilizer control system is verified. The simulations results show that the proposed UIO optimal fault diagnosis observer has the less state estimation error and faster convergence compared to traditional methods, and it can improve the effect of residual convergence and make a quick response to the system failure in the stage of fault diagnosis.

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孙蓉,刘胜,李冰.基于UIO的减摇鳍控制系统故障诊断算法[J].哈尔滨工业大学学报,2013,45(12):105. DOI:10.11918/j. issn.0367-6234.2013.12.019

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  • 收稿日期:2013-01-18
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  • 在线发布日期: 2014-01-06
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