This paper studies recursive optimal filtering as well as robust fault and state estimation for linear stochastic systems with unknown disturbances. It proposes a new recursive optimal filter structure with transformation of the original system. This transformation is based on the singular value decomposition of the direct feedthrough matrix distribution of the fault which is assumed to be of a...

Power System Fault Analysis Based on Intelligent Techniques and Intelligent Electronic Device Data. (May 2007) Xu Luo, B.S., Xi’an Jiaotong University; M.S., Xi’an Jiaotong University Chair of Advisory Committee: Dr. Mladen Kezunovic This dissertation has focused on automated power system fault analysis. New contributions to fault section estimation, protection system performance evaluation and...

This paper is concerned with the finite-horizon H∞ fault estimation problem for a class of nonlinear stochastic time-varying systems with both randomly occurring faults and fading channels. The system model (dynamical plant) is subject to Lipschitz-like nonlinearities and the faults occur in a random way governed by a set of Bernoulli distributed white sequences. The system measurements are tra...

In this paper, the finite-horizon H∞ fault estimation problem is investigated for a class of uncertain nonlinear time-varying systems subject to multiple stochastic delays. The randomly occurring uncertainties (ROUs) enter into the system due to the random fluctuations of network conditions. The measured output is quantized by a logarithmic quantizer before being transmitted to the fault estima...

Real time and accurate fault detection has attracted an increasing attention with a growing demand for higher operational efficiency and safety of industrial gas turbines as complex engineering systems. Current methods based on condition monitoring data have drawbacks in using both expert knowledge and quantitative information for detecting faults. On account of this reason, this paper proposes...

The problem of unknown input estimation and compensation is studied for actuated nonlinear systems with noisy measurements. The proposed solution is based on high order sliding-mode differentiation and discretetime optimization technique. Accuracy of the proposed hybrid estimation scheme is evaluated and stability of the compensating mechanism is established. It is shown that the fault detectio...

This paper presents a new observer design methodology for a time varying actuator fault estimation. A new linear matrix inequality (LMI) design algorithm is developed to tackle the limitations (e.g. equality constraint and robustness problems) of the well known so called fast adaptive fault estimation observer (FAFE). The FAFE is capable of estimating a wide range of time-varying actuator fault...

This paper considers the design of robust`1 estimators based on multiplier theory (which is intimately related to the mixed structured singular value theory) and the application of robust`1 estimators to robust fault detection. The key to estimator-based, robust fault detection is to generate residuals which are robust against plant uncertainties and external disturbance inputs, which in turn r...

This paper presents a method for fault detection and diagnosis of actuator loss of effectiveness for a quadrotor helicopter. This paper not only considers the detection of the actuator loss of effectiveness faults, but also addresses the diagnosis of the faults. The detection and estimation of the faults are performed by the Augmented Extended Kalman Filter. The faults are modelled as random wa...