Sensor Fault Diagnosis and Fault-Tolerant Control for Non-Gaussian Stochastic Distribution Systems

A sensor fault diagnosis method based on learning observer is proposed for non-Gaussian stochastic distribution control (SDC) systems. First, the system is modeled, and the linear B-spline is used to approximate the probability density function (PDF) of the system output. Then a new state variable is introduced, and the original system is transformed to an augmentation system. The observer is designed for the augmented system to estimate the fault. The observer gain and unknown parameters can be obtained by solving the linear matrix inequality (LMI). The fault influence can be compensated by the fault estimation information to achieve fault-tolerant control. Sliding mode control is used to make the PDF of the system output to track the desired distribution. MATLAB is used to verify the fault diagnosis and fault-tolerant control results.

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Fault Diagnosis and Fault Tolerant Control for Non-Gaussian Singular Time-Delayed Stochastic Distribution Systems

Mathematical Problems in Engineering ◽

10.1155/2014/937583 ◽

2014 ◽

Vol 2014 ◽

pp. 1-9 ◽

Cited By ~ 1

Author(s):

Lina Yao ◽

Long Feng ◽

Bin Jiang

Keyword(s):

Fault Diagnosis ◽

Distribution Systems ◽

Fault Tolerant ◽

Fault Tolerant Control ◽

Fault Estimation ◽

Control Input ◽

Observation Error ◽

Non Gaussian ◽

Stochastic Distribution ◽

Singular Time

New integrated fault diagnosis (FD) and fault tolerant control (FTC) algorithm for non-Gaussian singular time-delayed stochastic distribution control (SDC) system is proposed in the paper. Different from general SDC systems, in singular time-delayed SDC systems, the relationship between the weights and the control input is expressed by a singular time-delayed state space model, which largely increases the difficulty in the FD and FTC design. An iterative learning observer (ILO) is designed to carry out the fault estimation. The influence of the time delay term is eliminated in the process of the proof of the observation error stability. The fault may be constant, slow varying, or fast varying. Combined with the switching control theory, based on the estimated fault information, the fault tolerant controller can be designed to make the postfault probability density function (PDF) still track the given distribution. Simulations are given to show the effectiveness of the proposed integrated FD and FTC algorithms.

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Fault Diagnosis and Fault Tolerant Control for Non-Gaussian Singular Time-Delayed Stochastic Distribution Systems with Disturbance Based on the Rational Square-Root Model

Journal of Control Science and Engineering ◽

10.1155/2016/9563481 ◽

2016 ◽

Vol 2016 ◽

pp. 1-11 ◽

Cited By ~ 1

Author(s):

Yuancheng Sun ◽

Zhanhong Liang

Keyword(s):

Fault Diagnosis ◽

Distribution Systems ◽

Fault Tolerant ◽

Tracking Error ◽

Fault Tolerant Control ◽

Adaptive Observer ◽

Square Root ◽

Non Gaussian ◽

Stochastic Distribution ◽

Singular Time

For the non-Gaussian singular time-delayed stochastic distribution control (SDC) system with unknown external disturbance where the output probability density function (PDF) is approximated by the rational square-root B-spline basis function, a robust fault diagnosis and fault tolerant control algorithm is presented. A full-order observer is constructed to estimate the exogenous disturbance and an adaptive observer is used to estimate the fault size. A fault tolerant tracking controller is designed using the feedback of distribution tracking error, fault, and disturbance estimation to let the postfault output PDF still track desired distribution. Finally, a simulation example is included to illustrate the effectiveness of the proposed algorithms and encouraging results have been obtained.

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