Robust fault detection based on multimodel and interval approach. Application to a throttle valve

A multimodel approach has been set up in this paper. The purpose is to replace a nonlinear system by a linear one combined with interval analysis approach in order to take into account uncertainties in the model. Linear systems can be easily handled with interval computation. However, nonlinear systems need complex computations as set-computation based on sub-paving algorithms for example. To avoid a large amount of computation, the approach proposed herein is to decompose a nonlinear system in several linear models. Uncertain systems can take advantages of this approach called multimodel approach. In this paper a robust fault detection method based on multimodel will be presented. The detection will be made by an Interval Set-Valued Observer. The system is nonlinear and represents a throttle valve. It will be shown how the proposed method can replace advantageously an identification step by taking into account uncertainties on parameters.

[1]  A. Willsky,et al.  Analytical redundancy and the design of robust failure detection systems , 1984 .

[2]  Jie Chen,et al.  Robust Model-Based Fault Diagnosis for Dynamic Systems , 1998, The International Series on Asian Studies in Computer and Information Science.

[3]  E. Walter,et al.  Applied Interval Analysis: With Examples in Parameter and State Estimation, Robust Control and Robotics , 2001 .

[4]  Rolf Isermann,et al.  Process fault detection based on modeling and estimation methods - A survey , 1984, Autom..

[5]  Vicenç Puig,et al.  ROBUST FAULT DETECTION USING INTERVAL CONSTRAINTS SATISFACTION AND SET COMPUTATIONS 1 , 2006 .

[6]  Janos Gertler,et al.  Fault detection and diagnosis in engineering systems , 1998 .

[7]  Ali Zolghadri,et al.  Interval observer design for consistency checks of nonlinear continuous-time systems , 2010, Autom..

[8]  Paul M. Frank,et al.  Fault Diagnosis in Dynamic Systems , 1993, Robotics, Mechatronics and Manufacturing Systems.

[9]  Alex M. Andrew,et al.  Applied Interval Analysis: With Examples in Parameter and State Estimation, Robust Control and Robotics , 2002 .

[10]  Vicenç Puig,et al.  ROBUST FAULT ISOLATION USING NON-LINEAR INTERVAL OBSERVERS: THE DAMADICS BENCHMARK CASE STUDY , 2005 .

[11]  Mohamed el Hadi Lebbal Contribution à la modélisation et au diagnostic des systèmes à commutations , 2006 .

[12]  José Ragot,et al.  Soft Computing Algorithm to Data Validation in Aerospace Systems Using Parity Space Approach , 2007 .

[13]  Didier Maquin,et al.  Diagnosis of an uncertain static system , 2000, Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No.00CH37187).

[14]  Dan T. Horak,et al.  Failure Detection and Isolation Methodology , 1990, 1990 American Control Conference.

[15]  Dimitri Lefebvre,et al.  MODELING AND IDENTIFICATION OF NON-LINEAR SYSTEMS BY A MULTIMODEL APPROACH : APPLICATION TO A THROTTLE VALVE , 2007 .