不确定时滞系统增益型故障的检测与估计被引量：6

Gain Fault Detection and Identification for Uncertain Time-delay Systems

下载PDF

导出

摘要针对一类不确定连续线性定常时滞系统,提出了一种执行器、传感器增益故障的鲁棒检测与估计策略。该类系统含有多状态与输出时滞,状态和输出方程上同时作用有非结构有界未知扰动。在Trunov和Polycarpou方法的基础上,设计了一种新的时滞系统自适应观测器用于检测并估计突变或缓变的增益故障。与Wang等针对线性无时滞不含输出扰动系统的工作相比,该结论更具一般性。理论分析表明,该方法对于未知扰动鲁棒,能够保证故障的估计,状态与输出估计偏差一致有界。数值仿真验证了方法的有效性。 A robust fault detection and identification scheme for actuator and sensor gain faults is proposed for continuous linear time-invariant systems with unstructured unknown inputs and multiple discrete delays in the state and output. Based on the scheme of Trunov and Polycarpou,a novel adaptive observer for time-delay systems is designed to detect and identify the faults that are either abrupt or incipient.Compared with Wang et al the work for delayfree systems without output disturbances,the result is more general.Robustness with respect to unknown disturbances is rigorously analyzed.The fault estimates,the state and output estimation errors are uniformly bounded as demonstrated.Numerical examples show that it is effective.

作者姜苍华周东华

机构地区清华大学自动化系

出处《控制工程》 CSCD 2005年第4期349-353,共5页 Control Engineering of China

基金国家自然科学基金资助项目(60234010) 国家973计划资助项目(2002CB312200)

关键词故障检测与估计线性时滞系统增益故障执行器与传感器故障未知扰动自适应观测器 fault detection and identification linear time-delay systems gain faults actuator and sensor faults unknown disturbances adaptive observers

分类号 TP273 [自动化与计算机技术—检测技术与自动化装置]

引文网络
相关文献

参考文献7

1Yang H, Saif M. Observer design and fault diagnosis for stateretarded dynamical systems [ J ]. Automatica, 1998, 34 (2):217-227.
2DingSX, ZhongM, TangB, et al. An LMI approach to the design of fault detection filter for time-delay LTI systems with unknown inputs [ A ]. Proceedings of the American Control Conference[ C ]. Arlington VA: IEEE,2001.
3Jiang B, Staroswiecki M, Cocquempot V. Fault identification for a class of time-delay systems [ A ]. Proceedings of the American Control Conference [ C ]. Anchorage AK: IEEE,2002.
4Wang H, Huang Z J, Daley S. On the use of adaptive updating rules for actuator and sensor fault diagnosis[J]. Automatica, 1997, 33(2) :217-225.
5Trunov A B, Polycarpou M M. Automated fault diagnosis in nonlinear multivariable systems using a learning methodology [J]. IEEE Transactions on Neural Networks, 2000, 11 ( 1 ):91-101.
6Hale J K, Verduyn Lunel S M.Introduction to functional differential equations[ M]. New York: Springer-verlag, 1993.
7Ioannou P A, Sun J.Robust adaptive control[M].Upper Saddle River: Prentice-hall, 1996.