Observer-based fault detection for uncertain nonlinear systems

Han, Huayun; Yang, Ying; Li, Linlin; Ding, Steven X.

doi:10.1016/j.jfranklin.2017.12.021

Cited by 26 publications

(11 citation statements)

References 42 publications

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“…Remark 3: For the sake of FDI, the matrix L can be chosen to satisfy (18) with the observer order q as low as possible.…”

Section: A Functional Observer Designmentioning

confidence: 99%

“…FDI Algorithm 1. Check condition (18). If condition ( 18) is satisfied, solve the LMI ( 25) and obtain matrix K = P −T 2 Y .…”

Section: Residual Generators For Fault Isolationmentioning

confidence: 99%

“…The design and analysis of fault diagnosis schemes for different classes of dynamic systems have been studied extensively over the past decades [14]- [21]. Many works mainly focus on the problem of fault detection such as fault detection problem for nonlinear systems was investigated in [16]- [18], an iterative approach to H − /H ∞ fault detection observer design for discrete-time uncertain systems was proposed in [15]. Considerable effort also has been devoted to the development of fault detection and isolation (FDI) problem.…”

Section: Introductionmentioning

confidence: 99%

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Functional Observer Design for Time-Delayed Systems With Application to Fault Diagnosis

2019

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This paper deals with the functional observer (FO)-based fault detection and isolation problem for time-delayed linear systems. First, a new method to design the low-order FO estimating the partial states for linear systems with time-varying delay is presented. Conditions for the existence of the proposed observer and the stability of resulting error dynamics are derived. Based on the proposed observer, a novel residual generator is constructed to detect actuator faults. Furthermore, a bank of residual generators for fault isolation is also constructed for time-delayed systems. The simulation results of the numerical example demonstrate that the proposed observer-based fault diagnosis scheme works effectively.

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“…Remark 3: For the sake of FDI, the matrix L can be chosen to satisfy (18) with the observer order q as low as possible.…”

Section: A Functional Observer Designmentioning

confidence: 99%

“…FDI Algorithm 1. Check condition (18). If condition ( 18) is satisfied, solve the LMI ( 25) and obtain matrix K = P −T 2 Y .…”

Section: Residual Generators For Fault Isolationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Functional Observer Design for Time-Delayed Systems With Application to Fault Diagnosis

2019

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“…As a result, numerous FD and FTC approaches have been proposed not only for linear systems but also for nonlinear systems . Among the publications on nonlinear FD and FTC problems, special types of nonlinearities have been intensively studied, for instance, Lipschitz nonlinearity, affine nonlinearity, and sector‐bounded nonlinearity . In addition, there have been literatures addressing system performance such as the tracking performance, robustness performance, as well as H ∞ performance .…”

Section: Introductionmentioning

confidence: 99%

Control performance‐based fault detection and fault‐tolerant control schemes for a class of nonlinear systems

Han

Chen

et al. 2019

Intl J Robust & Nonlinear

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Summary The objective of this paper is to develop performance‐based fault detection (FD) and fault‐tolerant control (FTC) schemes for a class of nonlinear systems. To this end, the representation forms of nonlinear systems with faults and the controller parameterization forms are studied first with the aid of the nonlinear factorization technique. Then, based on the stable kernel representation and the stable image representation of the faulty nonlinear system, the stability performance of the closed‐loop system is addressed, respectively. The so‐called fault‐tolerant margin is defined to evaluate the system fault‐tolerant ability. On this basis, two performance‐based FD schemes are developed aiming at detecting the system performance degradation caused by system faults. Furthermore, to recover the system stability performance, two performance‐based FTC strategies are proposed based on the information provided by the FD unit. In the end, a numerical example and a case study on the three‐tank system are given to demonstrate the proposed results.

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“…1.1 Introduction: robust control of uncertain systems Furthermore, if the search is focused on specic application areas, it is found that robust controllers specically DOBCs, ADRCs and sliding mode controllers are being applied in: motion control (Umeno et al 1991;Choi et al 1999;Sariyildiz et al 2015), power electronics (Yokoyama et al 1994;Jain et al 2020), fault diagnosis (Wang et al 1996;Han et al 2018;Bernardi et al 2020), automobiles (Bünte et al 2002;Kadowaki et al 2002;Fujimoto et al 2004), underwater vehicles (Peng et al 2017), networks (Natori et al 2008), missile seekers (Sadhu et al 2010), spacecrafts (Liu et al 2018), UAVs (Castillo et al 2019a), surgery/rehabilitation robots (Ugurlu et al 2014), long-distance laser positioning (Deng et al 2020) and magnetic levitation (Yang et al 2011); among many others.…”

Section: Prefacimentioning

confidence: 99%

Novel Strategies to design Controllers and State Predictors based on Disturbance Observers

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Observer-based fault detection for uncertain nonlinear systems

Cited by 26 publications

References 42 publications

Functional Observer Design for Time-Delayed Systems With Application to Fault Diagnosis

Functional Observer Design for Time-Delayed Systems With Application to Fault Diagnosis

Control performance‐based fault detection and fault‐tolerant control schemes for a class of nonlinear systems

Novel Strategies to design Controllers and State Predictors based on Disturbance Observers

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