Diagnostic des systèmes à changement de régime de fonctionnement

Les systemes a commutation representent une classe particuliere de systemes hybrides. Ils sont decrits par plusieurs modeles de fonctionnement et chaque modele, definissant un mode du systeme, est actif sous certaines conditions operatoires particulieres. Lorsque la loi de commutation regissant le passage d'un modele de fonctionnement a l'autre est parfaitement connue, il est aise de manipuler de tels systemes car le mode actif peut etre connu a chaque instant. Par contre, dans la situation ou aucune information n'est disponible sur l'evolution de la loi de commutation, il est plus ardu de proceder au diagnostic ou encore de synthetiser une loi de commande sur ces systemes. Il est aborde ici le probleme de la reconnaissance du mode actif sur la base d'observations de l'entree et de la sortie du systeme. L'identification des parametres de la loi de commutation est ensuite etudiee sous l'hypothese de la connaissance de la structure de la loi de commutation.

[1]  Simon M. Potter.  A Nonlinear Approach to US GNP , 1995 .

[2]  Don R. Hush,et al.  Efficient algorithms for function approximation with piecewise linear sigmoidal networks , 1998, IEEE Trans. Neural Networks.

[3]  S. Goldfeld,et al.  A Markov model for switching regressions , 1973 .

[4]  Yakov Ben-Haim,et al.  An Algorithm for Failure Location in a Complex Network , 1980 .

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

[6]  Jitendra K. Tugnait,et al.  Detection and estimation for abruptly changing systems , 1981, 1981 20th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes.

[7]  José Ragot,et al.  STRUCTURE IDENTIFICATION OF MULTIPLE MODELS WITH OUTPUT ERROR LOCAL MODELS , 2002 .

[8]  Manfred Morari,et al.  A clustering technique for the identification of piecewise affine systems , 2001, Autom..

[9]  M. Aubrun,et al.  Fault diagnosis in systems using directional residuals , 1994, Proceedings of 1994 33rd IEEE Conference on Decision and Control.

[10]  Thomas A. Henzinger,et al.  Hybrid systems III : verification and control , 1996 .

[11]  C. Granger,et al.  Modelling Nonlinear Economic Relationships , 1995 .

[12]  Alfredo C. Desages,et al.  Canonical piecewise-linear approximation of smooth functions , 1998 .

[13]  Inseok Hwang,et al.  Observability criteria and estimator design for stochastic linear hybrid systems , 2003, 2003 European Control Conference (ECC).

[14]  Didier Maquin,et al.  Parameter estimation of switching piecewise linear system , 2003, 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475).

[15]  P. Julián,et al.  High-level canonical piecewise linear representation using a simplicial partition , 1999 .

[16]  A. Alessandri,et al.  Design of observers for switched discrete-time linear systems , 2003, Proceedings of the 2003 American Control Conference, 2003..

[17]  A. Juloski,et al.  Data-based hybrid modelling of the component placement process in pick-and-place machines , 2004 .

[18]  Paul M. Frank,et al.  Issues of Fault Diagnosis for Dynamic Systems , 2010, Springer London.

[19]  Chong-Ho Choi,et al.  Constructive neural networks with piecewise interpolation capabilities for function approximations , 1994, IEEE Trans. Neural Networks.

[20]  Robert J. Elliott,et al.  Filters for estimating Markov modulated poisson processes and image-based tracking , 1997, Autom..

[21]  Annie Bessot.  Geometry at Work , 2000 .

[22]  M. Morari,et al.  A survey on stability analysis of discrete-time piecewise affine systems , 2005 .

[23]  A. Alessandri,et al.  Switching observers for continuous-time and discrete-time linear systems , 2001, Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148).

[24]  R. Quandt.  The Estimation of the Parameters of a Linear Regression System Obeying Two Separate Regimes , 1958 .

[25]  S. Ernst,et al.  Hinging hyperplane trees for approximation and identification , 1998, Proceedings of the 37th IEEE Conference on Decision and Control (Cat. No.98CH36171).

[26]  Lennart Ljung,et al.  Construction of Composite Models from Observed Data , 1992 .

[27]  Rolf Isermann.  Estimation of Physical Parameters for Dynamic Processes with Application to an Industrial Robot , 1990, 1990 American Control Conference.

[28]  Eduardo Sontag.  Nonlinear regulation: The piecewise linear approach , 1981 .

[29]  O. Mangasarian,et al.  Multicategory discrimination via linear programming , 1994 .

[30]  Angelo Alessandri,et al.  Design of Luenberger Observers for a Class of Hybrid Linear Systems , 2001, HSCC.

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

[32]  Michèle Basseville,et al.  Detection of abrupt changes: theory and application , 1993 .

[33]  Leo Breiman,et al.  Hinging hyperplanes for regression, classification, and function approximation , 1993, IEEE Trans. Inf. Theory.

[34]  A. Juloski,et al.  Two approaches to state estimation for a class of piecewise affine systems , 2003, 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475).

[35]  Janos Gertler,et al.  Generating Directional Residuals with Dynamic Parity Equations , 1993 .

[36]  J. Lagarias,et al.  The finiteness conjecture for the generalized spectral radius of a set of matrices , 1995 .

[37]  Robin J. Evans,et al.  Image-enhanced multiple model tracking , 1999, Autom..

[38]  H. Tong,et al.  ON ESTIMATING THRESHOLDS IN AUTOREGRESSIVE MODELS , 1986 .

[39]  Vincent Cocquempot,et al.  Switching Time Estimation and Fault Detection for Hybrid Systems Using Structured Parity Residuals , 2003 .

[40]  Manfred Morari,et al.  Moving horizon estimation for hybrid systems , 2002, IEEE Trans. Autom. Control..

[41]  L. Chua,et al.  A global representation of multidimensional piecewise-linear functions with linear partitions , 1978 .

[42]  M. Resende,et al.  A Combinatorial Approach to Piecewise Linear Time Series Analysis , 2002 .

[43]  P. Grieder,et al.  Low complexity control of piecewise affine systems with stability guarantee , 2004, Proceedings of the 2004 American Control Conference.

[44]  Arnaud Doucet,et al.  Particle filters for state estimation of jump Markov linear systems , 2001, IEEE Trans. Signal Process..

[45]  Bart De Schutter,et al.  Optimal Control of a Class of Linear Hybrid Systems with Saturation , 1999, SIAM J. Control. Optim..

[46]  Olivier Adrot.  Diagnostic à base de modèles incertains utilisant l'analyse par intervalles : l'approche borante , 2000 .

[47]  James D. Hamilton.  A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle , 1989 .

[48]  B. Schutter,et al.  Model predictive control for max-min-plus-scaling systems , 2001, Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148).

[49]  Alberto Bemporad,et al.  Observability and controllability of piecewise affine and hybrid systems , 2000, IEEE Trans. Autom. Control..

[50]  Kristin P. Bennett,et al.  Multicategory Classification by Support Vector Machines , 1999, Comput. Optim. Appl..

[51]  J. Gertler.  Structured Residuals for Fault Isolation, Disturbance Decoupling and Modelling Error Robustness , 1992 .

[52]  C. Granger,et al.  Improved methods of combining forecasts , 1984 .

[53]  J. Gertler,et al.  Optimal residual decoupling for robust fault diagnosis , 1995 .

[54]  Magnus Egerstedt,et al.  ASYMPTOTIC OBSERVERS FOR DISCRETE-TIME SWITCHED LINEAR SYSTEMS , 2005 .

[55]  Arjan van der Schaft,et al.  Complementarity modelling of hybrid systems , 1997 .

[56]  A. Morse,et al.  Stability of switched systems: a Lie-algebraic condition ( , 1999 .

[57]  John N. Tsitsiklis,et al.  Complexity of stability and controllability of elementary hybrid systems , 1999, Autom..

[58]  Edward Yik Chow.  A failure detection system design methodology , 1980 .

[59]  S. Billings,et al.  Piecewise linear identification of non-linear systems , 1987 .

[60]  Hung Man Tong,et al.  Threshold models in non-linear time series analysis. Lecture notes in statistics, No.21 , 1983 .

[61]  Wpmh Maurice Heemels,et al.  Hybrid Systems: Computation and Control , 2003 .

[62]  Eberhard Münz,et al.  Identification of hybrid systems using a priori knowledge , 2002 .

[63]  Silvio Simani,et al.  Model-based fault diagnosis in dynamic systems using identification techniques , 2003 .

[64]  Gonzalo R. Arce,et al.  Piecewise linear system modeling based on a continuous threshold decomposition , 1996, IEEE Trans. Signal Process..

[65]  Alberto Bemporad,et al.  Control of systems integrating logic, dynamics, and constraints , 1999, Autom..

[66]  Roderick Murray-Smith,et al.  Multiple Model Approaches to Modelling and Control , 1997 .

[67]  Frédéric Kratz,et al.  Finite Memory Observer for State Estimation of Hybrid System , 2003 .

[68]  Manfred Morari,et al.  Complexity reduction of receding horizon control , 2003, 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475).

[69]  Mark R. Greenstreet,et al.  Hybrid Systems: Computation and Control , 2002, Lecture Notes in Computer Science.

[70]  S. Paoletti.  IDENTIFICATION OF PIECEWISE AFFINE MODELS , 2004 .

[71]  Alberto L. Sangiovanni-Vincentelli,et al.  Design of Observers for Hybrid Systems , 2002, HSCC.

[72]  F. Rosenqvist,et al.  Realisation and estimation of piecewise-linear output-error models , 2005, Autom..

[73]  Vikram Krishnamurthy,et al.  Adaptive nonlinear filters for narrow-band interference suppression in spread-spectrum CDMA systems , 1999, IEEE Trans. Commun..

[74]  Ray C. Fair,et al.  Methods of Estimation for Markets in Disequilibrium , 1972 .

[75]  Richard Vernon Beard,et al.  Failure accomodation in linear systems through self-reorganization. , 1971 .

[76]  H. Chizeck,et al.  Controllability, observability and discrete-time markovian jump linear quadratic control , 1988 .

[77]  Vladimir N. Vapnik,et al.  The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.

[78]  D. Hudson.  Fitting Segmented Curves Whose Join Points Have to Be Estimated , 1966 .

[79]  M. Mariton,et al.  Stochastic observability of linear systems with Markovian jumps , 1986, 1986 25th IEEE Conference on Decision and Control.

[80]  Abderrahmane Haddad,et al.  On the observability of linear stochastic switching systems , 1994, Proceedings of 1994 American Control Conference - ACC '94.

[81]  Jan-Erik Strömberg,et al.  Trees as Black-Box Model Structures for Dynamical Systems , 1990 .

[82]  J. K. Bhattacharjee,et al.  Modelling of Complex Systems , 1997 .

[83]  Olvi L. Mangasarian,et al.  Arbitrary-norm separating plane , 1999, Oper. Res. Lett..

[84]  S. Sastry,et al.  An algebraic geometric approach to the identification of a class of linear hybrid systems , 2003, 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475).

[85]  Jakob Roll.  Local and Piecewise Affine Approaches to System Identification , 2003 .

[86]  P. Pucar,et al.  On the Hinge-Finding Algorithm for Hinging Hyperplanes , 1998, IEEE Trans. Inf. Theory.

[87]  A. Morse,et al.  Basic problems in stability and design of switched systems , 1999 .

[88]  James D. Hamilton.  Analysis of time series subject to changes in regime , 1990 .

[89]  Andrea Balluchi,et al.  A hybrid observer for the driveline dynamics , 2001, 2001 European Control Conference (ECC).

[90]  Didier Maquin,et al.  Switching Time Estimation of Piecewise Linear Systems. Application to Diagnosis , 2003 .

[91]  Sung Mo Kang,et al.  Section-wise piecewise-linear functions: Canonical representation, properties, and applications , 1977, Proceedings of the IEEE.

[92]  Paul M. Frank,et al.  Fault diagnosis in dynamic systems: theory and application , 1989 .

[93]  K. Ito,et al.  On State Estimation in Switching Environments , 1970 .