Jakob Stoustrup

Kemin Zhou

Robustness Issues in Fault Diagnosis and Fault Tolerant Control

Several procedures for sensor fault detection and isolation (FDI) applied to a simulated model of a commercial aircraft are presented. The main contributions of the paper are related to the design and the optimisation of two FDI schemes based on a linear polynomial method (PM) and the nonlinear geometric approach (NLGA). The FDI strategies are applied to the aircraft model, characterised by tight-coupled longitudinal and lateral dynamics. The robustness and the reliability properties of the residual generators related to the considered FDI techniques are investigated and verified by simulating a general aircraft reference trajectory. Extensive simulations exploiting the Monte Carlo analysis tool are also used for assessing the overall performance capabilities of the developed FDI schemes, in the presence of turbulence, measurement, and model errors. Comparisons with other disturbance-decoupling methods for FDI based on neural networks (NNs) and unknown input kalman filter (UIKF) are finally reported.

M. Benini

M. Bonf&#xE8;

P. Castaldi

W. Geri

S. Simani

Design and Analysis of Robust Fault Diagnosis Schemes for a Simulated Aircraft Model

This paper presents an enhanced robust control design structure to realise fault tolerance towards sensor faults suitable for multi-input-multi-output (MIMO) systems implementation. The proposed design permits fault detection and controller elements to be designed with considerations to stability and robustness towards uncertainties besides multiple faults environment on a common mathematical platform. This framework can also cater to systems requiring fast responses. A design example is illustrated with a fast, multivariable and unstable system, that is, the double inverted pendulum system. Results indicate the potential of this design framework to handle fast systems with multiple sensor faults.

S.S. Yang

J. Chen

Design and Assessment of a Multiple Sensor Fault Tolerant Robust Control System

The stability guaranteed active fault-tolerant control against actuators failures and plant uncertainties in networked control systems (NCSs) is addressed. A detailed design procedure is formulated as a convex optimization problem which can be efficiently solved by existing software. An illustrative example is given to show the efficiency of the proposed method for network-based control for uncertain systems.

Shanbin Li

Dominique Sauter

Christophe Aubrun

Joseph Yamé

Stability Guaranteed Active Fault-Tolerant Control of Networked Control Systems

In this contribution, an active fault-tolerant scheme that achieves fault detection, isolation, and accommodation is developed for LTI systems. Faults and perturbations are considered as additive signals that modify the state or output equations. The accommodation scheme is based on the generalized internal model control architecture recently proposed for fault-tolerant control. In order to improve the performance after a fault, the compensation is considered in two steps according with a fault detection and isolation algorithm. After a fault scenario is detected, a general fault compensator is activated. Finally, once the fault is isolated, a specific compensator is introduced. In this setup, multiple faults could be treated simultaneously since their effect is additive. Design strategies for a nominal condition and under model uncertainty are presented in the paper. In addition, performance indices are also introduced to evaluate the resulting fault-tolerant scheme for detection, isolation, and accommodation. Hard thresholds are suggested for detection and isolation purposes, meanwhile, adaptive ones are considered under model uncertainty to reduce the conservativeness. A complete simulation evaluation is carried out for a DC motor setup.

D. U. Campos-Delgado

E. Palacios

D. R. Espinoza-Trejo

Fault Detection, Isolation, and Accommodation for LTI Systems Based on GIMC Structure

This paper considers matrix inequality procedures to address the 
robust fault detection and isolation (FDI) problem for linear 
time-invariant systems subject to disturbances, faults, and 
polytopic or norm-bounded uncertainties. We propose a design 
procedure for an FDI filter that aims to minimize a weighted 
combination of the sensitivity of the residual signal to 
disturbances and modeling errors, and the deviation of the faults 
to residual dynamics from a fault to residual reference model, using the -norm as a measure. A key step in our
procedure is the design of an optimal fault reference model. We
show that the optimal design requires the solution of a quadratic
matrix inequality (QMI) optimization problem. Since the solution
of the optimal problem is intractable, we propose a linearization
technique to derive a numerically tractable suboptimal design
procedure that requires the solution of a linear matrix inequality
(LMI) optimization. A jet engine example is employed to
demonstrate the effectiveness of the proposed approach.

Emmanuel Mazars

Imad M. Jaimoukha

Zhenhai Li

Computation of a Reference Model for Robust Fault Detection and Isolation Residual Generation

This paper gives a review of some standard fault-detection (FD) problem formulations in discrete linear time-invariant systems and the available solutions. Based on it, recent development of FD in periodic systems and sampled-data systems is reviewed and presented. The focus in this paper is on the robustness and sensitivity issues in designing model-based FD systems.

P. Zhang

S. X. Ding

On Fault Detection in Linear Discrete-Time, Periodic, and Sampled-Data Systems

Actuator fault diagnosis is often studied under strong assumptions on available sensors.
Typically, it is assumed that the sensors are either fault free or sufficiently redundant. The
purpose of this paper is to present a new method for actuator fault diagnosis which is robust
to sensor distortion. It does not require sensor redundancy to compensate sensor distortion.
The essential assumption is that sensor distortions are strictly monotonous. Despite the
nonlinear and unknown nature of distortions, such sensors still provide useful information
for fault diagnosis. The robustness of the presented diagnosis method is analyzed, as well
as its ability to detect actuator faults. A numerical example is provided to illustrate its efficiency.

Qinghua Zhang

Actuator Fault Diagnosis with Robustness to Sensor Distortion

This paper considers robust fault-detection problems for linear discrete time systems. It is shown that the optimal robust detection filters for several well-recognized robust fault-detection problems, such as /, /, and / problems, are the same and can be obtained by solving a standard algebraic Riccati equatio
n. Optimal filters are also derived for many other optimization criteria and it is shown that some well-studied and seeming-sensible optimization criteria for fault-detection filter design could lead to (optimal) but useless fault-detection filters.

Nike Liu

Optimal Robust Fault Detection for Linear Discrete Time Systems

The work presented in this paper focuses on the design of robust Fault Detection and Isolation (FDI) filters for dynamic systems characterized by LPV (Linear Parameter Varying) polytopic models. A sufficient condition is established to guarantee sensitivity performance of the residual signal vector to faults. Robustness constraints against model perturbations and disturbances are also taken into account in the design method. A key feature of the proposed method is that the residual structuring matrices are optimized as an integral part of the design, together with the dynamic part (i.e. the filter). The design problem is formulated as a convex optimization problem and solved using LMI (Linear Matrix Inequalities) techniques. The proposed method is illustrated on the secondary circuit of a Nuclear Power Plant.

Sylvain Grenaille

David Henry

Ali Zolghadri

A Method for Designing Fault Diagnosis Filters for LPV Polytopic Systems

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Journal of Control Science and Engineering publishes research investigating the design, simulation and modelling, implementation, and analysis of methods and technologies for control systems and applications.

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Chief Editor, Professor Seiichiro Katsura, is based at Keio University, Japan. His laboratory is developing a novel synthesis method based on the infinite-order modeling and energy conversion of electromechanical integration systems.

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Journal of Control Science and Engineering

Robustness Issues in Fault Diagnosis and Fault Tolerant Control

Robustness Issues in Fault Diagnosis and Fault Tolerant Control

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