Simultaneous sensor and actuator fault estimation for continuous-time polytopic LPV system

Bedioui, Neila; Houimli, Radhia; Besbes, Mongi

doi:10.1080/00207721.2019.1599078

Cited by 18 publications

(8 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In order to estimate actuator and sensor faults simultaneously, the LPV system ( 6) is transformed by introducing z(t) ∈ R n y , which is a filtered version of y(t), 14,38 updated as ̇z(t) = E(y(t) − z(t)), where E is any Hurwitz matrix with appropriate dimensions, as shown in Figure 1.…”

Section: Preliminaries and Problem Descriptionmentioning

confidence: 99%

“…For example, Rodriguez et al 13 proposed an adaptable polytopic observer to estimate constant and time-varying actuator faults for LPV descriptor systems. Bedioui et al 14 developed a robust adaptive observer to estimate sensor and actuator faults. Brizuela et al 15 proposed to use an observer based on a polynomial LPV system for simultaneous actuator and sensor fault estimation.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Actuator and sensor fault estimation based on a proportional multiple‐integral sliding mode observer for linear parameter varying systems with inexact scheduling parameters

Gómez-Peñate

López‐Estrada

Valencia‐Palomo

et al. 2020

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

This article proposes an approach for the estimation of states, actuator, and sensor faults in nonlinear systems represented by a polytopic linear parameter varying (LPV) system with inexact scheduling parameters. In the traditional LPV approaches, the scheduling variables are considered to be perfectly known.However, in practical applications, their measurement may contain precision and calibration errors or noise that can affect the performance of the diagnostic systems. Therefore, this work proposes the design of a proportional multiple-integral sliding mode observer for fault diagnosis (FD) that copes with LPV systems with inexact scheduling parameters. Due to the introduction of some nonlinear functions, the proposed observer is a nonlinear parameter varying system for which stability and robustness performance are formulated using the Lyapunov technique and a H ∞ performance criterion. It is shown that the design conditions boil down to a set of linear matrix inequalities whose solution allows computing the observer gain matrix along with the tunable parameters of the nonlinear functions. Results obtained using the simulator of an octocopter-type unmanned aerial vehicle are used to demonstrate the applicability and performance of the proposed FD scheme. K E Y W O R D Sfault diagnosis, linear matrix inequalities, nonlinear parameter varying systems, proportional multiple-integral sliding mode observer INTRODUCTIONModern control systems are prone to faults, which can damage the systems themselves or the environments in which they operate. For this reason, fault diagnosis (FD) algorithms become essential, since they enable fault-tolerant actions that minimize the effect of faults and improve the overall system's reliability and safety. An FD algorithm can be seen as a two-step process in which at first the fault is detected, that is, a Boolean logic value about the presence of a fault is provided, 8420

show abstract

Section: Preliminaries and Problem Descriptionmentioning

confidence: 99%

mentioning

confidence: 99%

Actuator and sensor fault estimation based on a proportional multiple‐integral sliding mode observer for linear parameter varying systems with inexact scheduling parameters

Gómez-Peñate

López‐Estrada

Valencia‐Palomo

et al. 2020

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

show abstract

“…Many model-based methods [6] have been developed for detection and estimation of states and faults like parity space [7], parametric identification [8], and state estimation [9]. Among the most widespread are those based on observers that have been used with several system classes in the singular or explicit case and in continuous or discrete-time such as: linear parameter varying systems [10], piecewise linear systems [11], linear systems [12], uncertain systems [13], Lipschitz systems [14], and T-S models [2,[15][16][17][18][19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Observer Design for Fault Estimation for Discrete-time Takagi-Sugeno Singular Models with Unmeasurable Premise Variables

Ouarid¹,

Assoudi²,

Essabre³

et al. 2021

IJIES

View full text Add to dashboard Cite

This paper aims to present a new approach in the design of observers for a Class of Discrete-time Takagi-Sugeno Singular Models (DTTSM) in the case of unmeasurable premise variables, allowing to estimate simultaneously the states of the system, and the faults in the actuators and sensors. The approach used is based on augmenting the state vector. The exponential convergence is studied using the Lyapunov theory. The stability conditions are presented as Linear Matrix Inequalities (LMIs). Lastly, a numerical application is used to evaluate the efficiency of the proposed dynamic system. It shows that the estimated variables catch up rapidly (around 0.3s), and accurately the real variables during the application time of the actuator and sensor faults.

show abstract

“…Fault estimation, as a bridge between fault diagnosis step and tolerant control, is more challenging, and fruitful results were published in the literature in the last years. 28–33 For instance, Liu et al 28 proposed scheme integrating robust fault estimation design and FTC for T-S fuzzy models subject to simultaneous sensor faults, actuator faults, and partially decoupled unknown inputs. Hence, T-S fuzzy-based unknown input observers and robust optimization techniques are used to provide the estimation of the considered faults.…”

Section: Introductionmentioning

confidence: 99%

“…30,31 In Valibeygi et al, 32 an observer-based sensor fault estimation was constructed for generalized sector-bounded nonlinear systems in the presence of measurement noises. The problem of state estimation and both actuator and sensor fault estimation for linear polytopic parameter-varying system is investigated in Bedioui et al 33 However, in most of the existing researches, the estimated faults have been considered only in the actuator or the sensor or both actuator and sensor components. The faults in the parameter components are rarely considered.…”

Section: Introductionmentioning

confidence: 99%

Uncertain fault estimation using bicausal bond graph: Application to intelligent autonomous vehicle

Lounici

Touati

Adjerid

2019

Proceedings of the Institution of Mechanical Engineers, Part I:

View full text Add to dashboard Cite

This article addresses the fault detection and isolation problem of uncertain systems using the bond graph model–based approach. The latter provides through its causal and structural properties an automatic analytical redundancy relations generation. The numerical evaluation of analytical redundancy relations yields residuals, which are used to verify the coherence between the real system and reference behaviors describing the nominal operation. In fact, the residual is compared to its thresholds to detect the fault. In addition, the comparison between all fault signatures allows making a decision on fault isolation. Moreover, to isolate the faults that activate the same set of residuals, an additional residual must be calculated for each fault. This additional residual is the comparison between two estimations of the considered fault obtained using the sensitivity relations. However, due to the presence of uncertainties, errors can occur in the fault estimation allowing false decisions on fault isolation. The novelties and innovative interests in the present work are (1) to improve the fault estimation procedure based on the uncertainties modeling and bicausality notion, in order to overcome the problem related to errors in the estimated fault and (2) to suitably generate the isolation thresholds in a systematic way using the uncertain fault estimation procedure proposed in this article so that fault can be isolated successfully. The proposed methodology is studied under various scenarios via simulations over an electromechanical traction system corresponding to a quarter of intelligent autonomous vehicle, named RobuCar.

show abstract

Simultaneous sensor and actuator fault estimation for continuous-time polytopic LPV system

Cited by 18 publications

References 18 publications

Actuator and sensor fault estimation based on a proportional multiple‐integral sliding mode observer for linear parameter varying systems with inexact scheduling parameters

Actuator and sensor fault estimation based on a proportional multiple‐integral sliding mode observer for linear parameter varying systems with inexact scheduling parameters

Fuzzy Observer Design for Fault Estimation for Discrete-time Takagi-Sugeno Singular Models with Unmeasurable Premise Variables

Uncertain fault estimation using bicausal bond graph: Application to intelligent autonomous vehicle

Contact Info

Product

Resources

About