非高斯随机系统的故障诊断与容错控制
摘要
研究讨论了基于两步模糊建模的一类具有未知故障的非高斯随机分布系统的故障诊断与容错控制问题。采用T-S权值模型描述模糊权值动态与控制输入之间的非线性关系,用模糊逻辑逼近非高斯过程的输出概率密度函数(PDFs)。利用典型的投影算法,设计了自适应模糊滤波器,成功地估计了系统的故障规模。同时,也可以保证故障出现时的误差系统稳定性。此外,还可以利用凸优化算法构造反馈控制输入,所设计的优化算法可以获得满意的控制性能和稳定性。
引文
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[2]叶杨飞.基于两步模糊建模的随机分布系统故障分析及仿真研究[D].江苏:扬州大学,2016.
[3]Guo L,Wang H.Stochastic Distribution Control System Design:A Convex Optimization Approach[M].London,U.K.:Springer-Verlag,2010.
[4]Yi Y,Guo L,Wang H.Constrained PI tracking control for output probability distributions based on two-step neural networks[J].IEEE Trans.Circuits Syst.I,Reg.,2009,56(7):1416-1426.
[5]Forbes M G,Guay M,Forbes J F.Control design for first-order processes:Shaping the probability density of the process state[J].J.Process Control,2004,14(4),399-410.
[6]Guo L,Wang H.PID controller design for output PDFs of stochastic systems using linear matrix inequalities[J].IEEE Trans.Syst.,Man,Cybern.B,2005,35(1),65-71.
[7]Yi Y,Zheng W X,Guo L.Improved results on statistic information control with a dynamic neural network identifier[J].IEEE Trans.Circuits and Syst.,2013,60(11),816-820.
[8]Yi Y,Zheng W X.Decentralized PI tracking control for non-Gaussian large-scale interconnected distribution systems[J].Journal of the Franklin Institute,2016,353(1):235-255.