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

Hao Wang,Lina Yao

doi:10.1155/2019/5839576

Abstract

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.

Highlights

With the rapid development of modern science and technology, control systems have become more complex, largescale, and intelligent, which puts more demands on the control of engineering control systems [1, 2]
It is of great significance to carry out research on fault diagnosis and fault-tolerant control of stochastic distribution systems to improve its reliability and safety and avoid loss of personnel and property
In order to verify the effectiveness of the algorithm, the proposed method is applied to the process of molecular weight distribution (MWD) dynamic modeling and control, and a continuous stirring reactor (CSTR) is considered as an example

Summary

Introduction

With the rapid development of modern science and technology, control systems have become more complex, largescale, and intelligent, which puts more demands on the control of engineering control systems [1, 2]. It is of great significance to carry out research on fault diagnosis and fault-tolerant control of stochastic distribution systems to improve its reliability and safety and avoid loss of personnel and property. For fault-tolerant control of non-Gaussian stochastic distribution systems, two situations are considered: (1) the desired PDF is known; (2) the desired PDF is not known in advance. In literature [16], collaborative system fault diagnosis and model prediction fault-tolerant control for the stochastic distribution system are described. The research of sensor fault diagnosis and fault-tolerant control of non-Gaussian stochastic distribution system is rarely documented; the sensor fault is inevitable. It is very meaningful for the work to be carried out in this paper.

Model Description

Fault Diagnosis

Fault-Tolerant Control

A Simulation Example

Conclusions