共查询到4条相似文献,搜索用时 0 毫秒
1.
Shu‐Li Sun Jing Ma Nan Lv 《International Journal of Adaptive Control and Signal Processing》2008,22(10):932-948
Based on the optimal fusion estimation algorithm weighted by scalars in the linear minimum variance sense, a distributed optimal fusion Kalman filter weighted by scalars is presented for discrete‐time stochastic singular systems with multiple sensors and correlated noises. A cross‐covariance matrix of filtering errors between any two sensors is derived. When the noise statistical information is unknown, a distributed identification approach is presented based on correlation functions and the weighted average method. Further, a distributed self‐tuning fusion filter is given, which includes two stage fusions where the first‐stage fusion is used to identify the noise covariance and the second‐stage fusion is used to obtain the fusion state filter. A simulation verifies the effectiveness of the proposed algorithm. Copyright © 2008 John Wiley & Sons, Ltd. 相似文献
2.
Filter‐based fault detection and diagnosis using output PDFs for stochastic systems with time delays
Y. M. Zhang L. Guo H. Wang 《International Journal of Adaptive Control and Signal Processing》2006,20(4):175-194
In this paper, a fault detection and diagnosis (FDD) scheme is studied for general stochastic dynamic systems subjected to state time delays. Different from the formulation of classical FDD problems, it is supposed that the measured information for the FDD is the probability density function (PDF) of the system output rather than its actual value. A B‐spline expansion technique is applied so that the output PDF can be formulated in terms of the dynamic weights of the B‐spline expansion, by which a time delay model can be established between the input and the weights with non‐linearities and modelling errors. As a result, the concerned FDD problem can be transformed into a classic FDD problem subject to an uncertain non‐linear system with time delays. Feasible criteria to detect the system fault are obtained and a fault diagnosis method is further presented to estimate the fault. Simple simulations are given to demonstrate the efficiency of the proposed approach. Copyright © 2006 John Wiley & Sons, Ltd. 相似文献
3.
Qingzhi He Xiaowu Mu Guifang Cheng 《International Journal of Adaptive Control and Signal Processing》2022,36(1):17-37
This article investigates the novel finite time adaptive neural fault-tolerant controller (FTC) for strict-feedback switched stochastic systems under arbitrary switching signals and takes into actuator failures including loss of effectiveness faults and bias faults consideration concurrently. Neural networks are utilized to approximate the unknown external disturbance and internal dynamics. On the basis of Itô differential equation and backstepping technique, an adaptive neural finite time FTC method is put forward. It is attested that the closed-loop systems are semiglobal practical finite time stable in probability and the tracking effects are great. Finally, to further demonstrate the high efficiency of proposed control method, two simulation examples are given. 相似文献