Robust model-based fault diagnosis for dynamic systems

Journal of Control Science and Engineering, 2008

IFAC Proceedings Volumes, 1989

This paper outlines the theory of a design approach to the detection of faults in dynamic s y stems using the concept of the robust unknown input observer. The method whi c h is based on eigenstructure assignment makes use of invariance c on c epts applicable to uncertain systems. The paper provides an interpretation of the proc ess of r o bust residual generation together with the underlying principles and concepts. The eigenstructure ass i gnment approach makes use of the full design freed om that is available in a multivariable observer system. A careful choice of the observer left eigenvectors e nables a high degree of parity space de-coupling t o be achieved, giving rise to an efficient fault monitor which is capable of detecting and isolating sensor faults. A discrete time design example is given which is based on a flight control system. Graphical results demonstrate the disturbance de-coupling property of the fault monitor.

2009

In this paper, the robust fault diagnosis problem for non-linear systems considering both bounded parametric modelling errors and noises is addressed using constraints satisfaction. Combining available measurements with the model of the monitored system, a set of analytical redundancy relations (ARR), relating only known variables, can be derived. These relations will be used in the fault diagnosis procedure to check the consistency between the observed and the predicted system behaviour. When some inconsistency is detected, the fault isolation mechanism will be activated in order to provide an explanation of the possible cause. Finally, a fault estimation procedure is used to estimate the fault size. To illustrate the usefulness of the proposed approach, a case study based on a well-known four tanks system benchmark is used.

International Journal of Control, 2004

We are generating residuals for linear fault diagnosis and isolation which are . robust with respect to a large variety of additive disturbances, . working in closed-loop, even with uncertain parameters.

International …, 2006

This paper is concerned with fault detection and isolation in nonlinear dynamic systems. A structural decomposition of the system is made, using the criterion of robustness to unknown inputs. To achieve this decomposition, special mathematical tools are used. The algebraic nature of these tools permits a more general formulation of the residual generation problem. These mathematical tools are presented with illustrations and the unknown input-free decomposition method is described. Some aspects of the method are discussed, and solutions are proposed to improve the existing algorithm. An application on an academic example is also provided.

International Journal of Robust and Nonlinear …, 2002

This paper presents a range of optimization based approaches to fault diagnosis. A variety of fault diagnosis problems are reformulated in the so-called standard problem setup introduced in the literature on robust control. Once the standard problem formulations are given, the fault diagnosis problems can be solved by standard optimization techniques. The proposed methods include: (1) fault diagnosis (fault estimation, (FE)) for systems with model uncertainties;

Annals of Mathematics and Artificial Intelligence, 1994

Research on model-based diagnosis of technical systems has grown enormously in the last few years, producing new basic tools, new algorithms and also some applications. However, the majority of research has dealt with systems described by variables ranging in discrete domains (e.g., digital circuits), and only few attempts have been made at applying such techniques to continuous domains. Continuous systems are characterized by additional problems, such as the unavoidable sensor errors and the need for using more complex models which may consist of simultaneous non-linear equations. The distinctive feature of the approach we present in this paper is the integration of techniques well known in the field of numerical analysis and statistics (e.g., the solution of non-linear systems and the error propagation) with a dependency-recording technique based on ordering the equations and the variables of the model.

Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 2012

This survey of model-based fault diagnosis focuses on those methods that are applicable to aerospace systems. To highlight the characteristics of aerospace models, generic non-linear dynamical modelling from flight mechanics is recalled and a unifying representation of sensor and actuator faults is presented. An extensive bibliographical review supports a description of the key points of fault detection methods that rely on analytical redundancy. The approaches that best suit the constraints of the field are emphasized and recommendations for future developments in in-flight fault diagnosis are provided.

Proceedings of the 44th IEEE Conference on Decision and Control, 2005

Classical model-based fault detection schemes for linear multivariable systems require the definition of suitable residual functions. This paper shows the possibility of identifying residual generators even when the system model is unknown, by following a black-box approach. The result is obtained by using canonical input-output polynomial forms which lead to characterise in a straightforward fashion the basis of the subspace described by all possible residual generators. The performance of the proposed identification method is tested by means of Monte Carlo simulations.

1997

Abstract Techniques for diagnosing faults in hybrid systems that combine digital (discrete) supervisory controllers with analog (continuous) plants need to be different from those used for discrete or continuous systems. This paper presents a methodology for online tracking and diagnosis of hybrid systems. We demonstrate the effectiveness of the approach with experiments conducted on the fuel-transfer system of fighter aircraft