scholarly journals Fault Diagnosis and Minimum Rational Entropy Fault Tolerant Control of Stochastic Distribution Collaborative Systems

Entropy ◽  
2018 ◽  
Vol 20 (11) ◽  
pp. 820 ◽  
Author(s):  
Lina Yao ◽  
Wei Wu ◽  
Yunfeng Kang ◽  
Lifan Li
Keyword(s):  
Fault Tolerant ◽  
Fault Tolerant Control ◽  
Collaborative Systems ◽  
Collaborative Control ◽  
Control Scheme ◽  
Control Target ◽  
In Series ◽  
System Output ◽  
Output Probability ◽  
Stochastic Distribution

In this paper, a fault-tolerant control scheme is presented for a class of stochastic distribution collaborative control systems, which are composed of three subsystems connected in series to complete the control target. The radial basis function neural network is used to approximate the output probability density function of the third subsystem, which is also the output of the entire system. When fault occurs in the first subsystem, an adaptive diagnostic observer is designed to estimate the value of fault. However, the first subsystem does not have the ability of self-recovery, minimum rational entropy controllers are designed in the latter subsystems to compensate the influence of the fault and minimize the entropy of the system output. A numerical simulation is given to verify the effectiveness of the proposed scheme.

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

2019 ◽  
Vol 2019 ◽  
pp. 1-8
Author(s):  
Hao Wang ◽  
Lina Yao
Keyword(s):  
Fault Diagnosis ◽  
Distribution Systems ◽  
Fault Tolerant ◽  
Sliding Mode ◽  
Fault Tolerant Control ◽  
Fault Estimation ◽  
Sensor Fault ◽  
System Output ◽  
Non Gaussian ◽  
Stochastic Distribution

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.

A fault-tolerant control scheme within adaptive disturbance observer for hypersonic vehicle

2017 ◽  
Vol 233 (3) ◽  
pp. 1071-1088 ◽  
Author(s):  
Jun Zhou ◽  
Jing Chang ◽  
Zongyi Guo
Keyword(s):  
Disturbance Observer ◽  
Fault Tolerant ◽  
Sliding Mode ◽  
Fault Tolerant Control ◽  
Lyapunov Theory ◽  
Sliding Mode Controller ◽  
Performance Guarantees ◽  
Uncertain Model ◽  
Control Scheme ◽  
And Performance

The paper describes the design of a fault-tolerant control scheme for an uncertain model of a hypersonic reentry vehicle subject to actuator faults. In order to improve superior transient performances for state tracking, the proposed method relies on a back-stepping sliding mode controller combined with an adaptive disturbance observer and a reference vector generator. This structure allows for a faster response and reduces the overshoots compared to linear conventional disturbance observers based sliding mode controller. Robust stability and performance guarantees of the overall closed-loop system are obtained using Lyapunov theory. Finally, numerical simulations results illustrate the effectiveness of the proposed technique.

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