scholarly journals T-S Fuzzy Model-Based Fault Detection for Continuous Stirring Tank Reactor

Processes ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 2127
Author(s):  
Yanqin Wang ◽  
Weijian Ren ◽  
Zhuoqun Liu ◽  
Jing Li ◽  
Duo Zhang
Keyword(s):  
Fault Detection ◽  
Fuzzy Model ◽  
Linear Matrix ◽  
Chemical Production ◽  
Fault Detection Filter ◽  
Filter Performance ◽  
Performance Requirements ◽  
Error Dynamics ◽  
The Given ◽  
Detection Filter

Continuous stirring tank reactors are widely used in the chemical production process, which is always accompanied by nonlinearity, time delay, and uncertainty. Considering the characteristic of the actual reaction of the continuous stirring tank reactors, the fault detection problem is studied in terms of the T-S fuzzy model. Through a fault detection filter performance analysis, the sufficient condition for the filtering error dynamics is obtained, which meets the exponential stability in the mean square sense and the given performance requirements. The design of the fault detection filter is transformed into one that settles the convex optimization issue of linear matrix inequality. Numerical analysis shows the effectiveness of this scheme.

scholarly journals Unitary Approximations in Fault Detection Filter Design

2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Dušan Krokavec ◽  
Anna Filasová ◽  
Pavol Liščinský
Keyword(s):  
Transfer Function ◽  
Fault Detection ◽  
Filter Design ◽  
Mimo Systems ◽  
Singular Values ◽  
Linear Matrix ◽  
Fault Detection Filter ◽  
Design Requirements ◽  
Detection Filter ◽  
Function Matrix

The paper is concerned with the fault detection filter design requirements that relax the existing conditions reported in the previous literature by adapting the unitary system principle in approximation of fault detection filter transfer function matrix for continuous-time linear MIMO systems. Conditions for the existence of a unitary construction are presented under which the fault detection filter with a unitary transfer function can be designed to provide high residual signals sensitivity with respect to faults. Otherwise, reflecting the emplacement of singular values in unitary construction principle, an associated structure of linear matrix inequalities with built-in constraints is outlined to design the fault detection filter only with a Hurwitz transfer function. All proposed design conditions are verified by the numerical illustrative examples.

Robust Fault Detection for Network-Based System with Time-Varying Bounded Delay

2012 ◽  
Vol 503-504 ◽  
pp. 1389-1392
Author(s):  
Li Min Chen
Keyword(s):  
Fault Detection ◽  
Flight Control ◽  
Upper Bound ◽  
Filter Design ◽  
Estimation Error ◽  
Linear Matrix ◽  
Fault Detection Filter ◽  
Detection Approach ◽  
Robust Fault Detection ◽  
Detection Filter

A robust fault detection approach for network-based system is discussed in this paper. The fault detection problem is converted into fault detection filter design. The network-induced delay is assumed to have both the upper bound and the lower bound, which is more general compared with only considering the upper bound. The Lyapunov-Krasovskii functional and the linear matrix inequality (LMI)-based procedure are adopted to design the filter. And the filter can guarantee that the estimation error satisfies the H∞ constraint. Fault detection filter is designed for a flight control system and the effectiveness is verified by the simulation results.

Robust Fault Detection for Singular Stochastic Systems

2011 ◽  
Vol 128-129 ◽  
pp. 276-279 ◽  
Author(s):  
Ai Qing Zhang
Keyword(s):  
Fault Detection ◽  
Stochastic Systems ◽  
Detection System ◽  
Linear Matrix ◽  
Fault Detection Filter ◽  
Robust Fault Detection ◽  
Lyapunov Function Method ◽  
Singular Stochastic Systems ◽  
Residual Generator ◽  
Detection Filter

-This paper deals with the problem of fault detection filter (FDF) design for singular stochastic systems . By using an observer-based FDF as a residual generator,the robust fault detection is formulated as a filtering problem. Based on linear matrix inequalities (LMIS) techniques and stability theory of stochastic differential equations, stochastic Lyapunov function method is adopted to design a FDF such that, the filter residual system is sensitive to the fault but robust to the exogenous disturbance.Sufficient conditions are proposed to guarantee the stochastically mean-square stablility with an performance for the faulty detection system. The existence of a FDF for the system under consideration is achieved in terms of LMIS . Moreover, the expressions of desired fault detection filter are given.

Fault Detection Filter for Markov Jump Systems

2012 ◽  
Vol 503-504 ◽  
pp. 1488-1492 ◽  
Author(s):  
Yu Cai Ding ◽  
Hong Zhu ◽  
Shou Ming Zhong ◽  
Yu Ping Zhang
Keyword(s):  
Fault Detection ◽  
Transition Probabilities ◽  
Linear Matrix ◽  
Markov Jump ◽  
Markov Jump Systems ◽  
Fault Detection Filter ◽  
Partly Unknown Transition Probabilities ◽  
Attenuation Level ◽  
Jump Systems ◽  
Detection Filter

This paper deals with the problem of fault detection for Markov jump systems (MJSs) with time-varying delays and partly unknown transition probabilities. The aim of this paper is to design a fault detection filter such that the filtering error system is stochastically asymptotically stable with an attenuation level. By using the Lyapunov-Krasovskii functional, a sufficient condition for the existence of the desired fault detection filter is formulated in terms of linear matrix inequalities. A numerical example is given to illustrate the effectiveness of the proposed main results.

scholarly journals Fault Detection Filter Design for Stochastic Systems with Mixed Time-Delays and Parameter Uncertainties

2013 ◽  
Vol 2013 ◽  
pp. 1-11
Author(s):  
Liyuan Hou ◽  
Shouming Zhong ◽  
Hong Zhu ◽  
Yong Zeng ◽  
Lin Shi
Keyword(s):  
Fault Detection ◽  
Time Delays ◽  
Stochastic Systems ◽  
Filter Design ◽  
Main Idea ◽  
Linear Matrix ◽  
Parameter Uncertainties ◽  
Fault Detection Filter ◽  
Mixed Time Delays ◽  
Detection Filter

This paper purposes the design of a fault detection filter for stochastic systems with mixed time-delays and parameter uncertainties. The main idea is to construct some new Lyapunov functional for the fault detection dynamics. A new robustly asymptotically stable criterion for the systems is derived through linear matrix inequality (LMI) by introducing a comprehensive different Lyapunov-Krasovskii functional. Then, the fault detection filter is designed in terms of linear matrix inequalities (LMIs) which can be easily checked in practice. At the same time, the error between the residual signal and the fault signal is made as small as possible. Finally, an example is given to illustrate the effectiveness and advantages of the proposed results.

scholarly journals Fault Detection Filter Design of Polytopic Uncertain Continuous-Time Singular Markovian Jump Systems with Time-Varying Delays

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-23 ◽  
Author(s):  
Yunling Shi ◽  
Xiuyan Peng
Keyword(s):  
Fault Detection ◽  
Continuous Time ◽  
Linear Matrix ◽  
Time Varying ◽  
Markovian Jump ◽  
Reduced Order ◽  
Fault Detection Filter ◽  
Singular Markovian Jump Systems ◽  
Jump Systems ◽  
Detection Filter

This paper investigates the problem of full-order and reduced-order fault detection filter (FDF) design under unified linear matrix inequality (LMI) conditions for a class of continuous-time singular Markovian jump systems (CTSMJSs) with time-varying delays and polytopic uncertain transition rates. By constructing a new Lyapunov function, sufficient conditions are firstly provided for the singular model error augmented system such that the system is stochastically admissible with an H∞ performance level γ. And then, by applying a novel convex polyhedron technique to decoupled linear matrix inequalities, the full-order and reduced-order fault detection filter parameters can be obtained within a convex optimization frame. The reduced-order fault detection filter (FDF) can not only meet the fault detection accuracy requirements of complex systems but also improve the fault detection efficiency. Finally, a DC motor and an illustrative simulation example are given to verify the feasibility and effectiveness of the proposed algorithms.

scholarly journals Distributed Fault Detection for a Class of Nonlinear Stochastic Systems

2014 ◽  
Vol 2014 ◽  
pp. 1-8
Author(s):  
Bingyong Yan ◽  
Huazhong Wang ◽  
Huifeng Wang
Keyword(s):  
Fault Detection ◽  
Stochastic Systems ◽  
Linear Matrix ◽  
False Alarms ◽  
Nonlinear Stochastic Systems ◽  
Design Procedures ◽  
Fault Detection Filter ◽  
Consensus Filter ◽  
Distributed Fault Detection ◽  
Detection Filter

A novel distributed fault detection strategy for a class of nonlinear stochastic systems is presented. Different from the existing design procedures for fault detection, a novel fault detection observer, which consists of a nonlinear fault detection filter and a consensus filter, is proposed to detect the nonlinear stochastic systems faults. Firstly, the outputs of the nonlinear stochastic systems act as inputs of a consensus filter. Secondly, a nonlinear fault detection filter is constructed to provide estimation of unmeasurable system states and residual signals using outputs of the consensus filter. Stability analysis of the consensus filter is rigorously investigated. Meanwhile, the design procedures of the nonlinear fault detection filter are given in terms of linear matrix inequalities (LMIs). Taking the influence of the system stochastic noises into consideration, an outstanding feature of the proposed scheme is that false alarms can be reduced dramatically. Finally, simulation results are provided to show the feasibility and effectiveness of the proposed fault detection approach.

Full- and Reduced-Order Fault Detection Filter Design With Application in Flow Transmission Lines

2018 ◽  
Vol 141 (2) ◽  
Author(s):  
Saeed Salavati ◽  
Karolos Grigoriadis ◽  
Matthew Franchek ◽  
Reza Tafreshi
Keyword(s):  
Fault Diagnosis ◽  
Fault Detection ◽  
Filter Design ◽  
Sufficient Conditions ◽  
Fault Detection And Isolation ◽  
Linear Matrix ◽  
Reduced Order ◽  
Fault Detection Filter ◽  
Order Filter ◽  
Detection Filter

The full- and reduced-order fault detection filter design is examined for fault diagnosis in linear time-invariant (LTI) systems in the presence of noise and disturbances. The fault detection filter design problem is formulated as an H∞ problem using a linear fractional transformation (LFT) framework and the solution is based on the bounded real lemma (BRL). Necessary and sufficient conditions for the existence of the fault detection filter are presented in the form of linear matrix inequalities (LMIs) resulting in a convex problem for the full-order filter design and a rank-constrained nonconvex problem for the reduced-order filter design. By minimizing the sensitivity of the filter residuals to noise and disturbances, the fault detection objective is fulfilled. A reference model can be incorporated in the design in order to shape the desired performance of the fault detection filter. The proposed fault detection and isolation (FDI) framework is applied to detect instrumentation and sensor faults in fluid transmission and pipeline systems. To this end, a lumped parameter framework for modeling infinite-dimensional fluid transient systems is utilized and a low-order model is obtained to pursue the instrumentation fault diagnosis objective. Full- and reduced-order filters are designed for sensor FDI. Simulations are conducted to assess the effectiveness of the proposed fault detection approach.

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