Integrated Fault Diagnosis and Fault Tolerant Control Algorithm for Non-Gaussian Stochastic Distribution Systems
Integrated Fault Diagnosis and Fault Tolerant Control Algorithm for Non-Gaussian Stochastic Distribution Systems
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发表时间：
2014
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通讯作者：
Yao Li-n
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作者：
Yao Li-n
在本文中，提出了针对非高斯非线性随机分布控制系统的综合断层诊断和容忍控制算法。RBF神经网络观察者基于错误的断层诊断和PI跟踪容错的可耐受控制。使用根B-Spline模型来表示输出概率密度函数（PDF）。在设计的非线性神经网络观察者A的基础上开发了新的故障诊断算法，以诊断此类系统动态部分中的慢变化故障。对从故障检测和诊断阶段引起的误差动态进行了连接分析。随着故障诊断的信息，新的失误耐受控制的信息设计了基于PI跟踪策略的方案，以便在失误概率密度函数仍然可以跟踪给定的分布。给出了一个模拟示例来说明所提出的效率算法。
In this paper,an integrated fault diagnosis and fault tolerant control algorithm was proposed for a non-Gaussian nonlinear stochastic distribution control system.The RBF neural networks observer based fault diagnosis and PI tracking fault tolerant control were integrated to be designed.The rational square-root B-spline model was used to represent the output probability density function(PDF).On the basis of designed nonlinear neural network observer,a new fault diagnosis algorithm was developed to diagnose the slow-varying fault in the dynamic part of such systems.Convergency analysis was performed for the error dynamics raised from the fault detection and diagnosis phase.With the information of fault diagnosis,a new fault tolerant control scheme based on PI tracking strategy was designed so that the post-fault probability density function could still track the given distribution.A simulated example has been given to illustrate the efficiency of the proposed algorithms.