Detection of abrupt changes in dynamic systems

In this paper we present some of the basic ideas associated with the detection of abrupt changes in dynamic systems. Our presentation focuses on two classes of methods — multiple filter-based techniques and residual-based methods — and in far more detail on the multiple model and generalized likelihood ratio methods. Issues such as the effect of unknown onset time on algorithm complexity and structure and robustness to model uncertainty are discussed.

[1]  Michael Athans,et al.  A suboptimal estimation algorithm with probabilistic editing for false measurements with applications to target tracking with wake phenomena , 1977 .

[2]  Jitendra Tugnait,et al.  Adaptive estimation and identification for discrete systems with Markov jump parameters , 1981, 1981 20th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes.

[3]  R.J. McAulay,et al.  A Decision - Directed Adaptive Tracker , 1973, IEEE Transactions on Aerospace and Electronic Systems.

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

[5]  Christopher Storm Greene.  An analysis of the multiple model adaptive control algorithm , 1980, 1980 19th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes.

[6]  Alan S. Willsky,et al.  Two self-test methods applied to an inertial system problem. [estimating gyroscope and accelerometer bias , 1975 .

[7]  Jere Schenck Meserole,et al.  Detection filters for fault-tolerant control of turbofan engines , 1981 .

[8]  Jitendra K. Tugnait,et al.  A detection-estimation scheme for state estimation in switching environments , 1979, Autom..

[9]  Kenneth Michael. Keverian,et al.  Multiobject tracking by adaptive hypothesis testing , 1979 .

[10]  P. M. Newbold,et al.  Detection of Changes in the Characteristics of a Gauss-Markov Process , 1968, IEEE Transactions on Aerospace and Electronic Systems.

[11]  Alan S. Willsky,et al.  Nonlinear Generalized Likelihood Ratio Algorithms for Maneuver Detection and Estimation , 1982, 1982 American Control Conference.

[12]  George C. Verghese,et al.  Optimally robust redundancy relations for failure detection in uncertain systems , 1986, Autom..

[13]  D. Magill.  Optimal adaptive estimation of sampled stochastic processes , 1965 .

[14]  R. A. Mckern,et al.  A redundant strapdown inertial systems mechanization-SIRU , 1970 .

[15]  M. Basseville,et al.  Edge detection using sequential methods for change in level--Part I: A sequential edge detection algorithm , 1981 .

[16]  D. Lainiotis,et al.  Partitioning: A unifying framework for adaptive systems, I: Estimation , 1976, Proceedings of the IEEE.

[17]  A. Willsky,et al.  A generalized likelihood ratio approach to the detection and estimation of jumps in linear systems , 1976 .

[18]  P K Houpt,et al.  Dynamic model-based techniques for the detection of incidents on freeways , 1980 .

[19]  Alan S. Willsky,et al.  F-8 DFBW sensor failure identification using analytic redundancy , 1977 .

[20]  A. Benveniste,et al.  Desgin and comparative study of some sequential jump detection algorithms for digital signals , 1983 .

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

[22]  R. K. Mehra,et al.  Correspondence item: An innovations approach to fault detection and diagnosis in dynamic systems , 1971 .

[23]  Harry L. Van Trees,et al.  Detection, Estimation, and Modulation Theory, Part I , 1968 .

[24]  Harold Lee Jones,et al.  Failure detection in linear systems , 1973 .

[25]  Donald E. Gustafson,et al.  ECG/VCG Rhythm Diagnosis Using Statistical Signal Analysis-I. Identification of Persistent Rhythms , 1978, IEEE Transactions on Biomedical Engineering.

[26]  Robert R. Tenney,et al.  A tracking filter for maneuvering sources , 1977 .

[27]  Robert Broen.  A nonlinear voter-estimator for redundant systems , 1974, CDC 1974.

[28]  M. Basseville,et al.  Edge detection using sequential methods for change in level--Part II: Sequential detection of change in mean , 1981 .

[29]  Michael Athans,et al.  The stochastic control of the F-8C aircraft using a multiple model adaptive control (MMAC) method--Part I: Equilibrium flight , 1977 .

[30]  Yoram Baram,et al.  Information, consistent estimation and dynamic system identification , 1977 .

[31]  Christopher D. Wickens,et al.  Failure Detection in Dynamic Systems , 1981 .

[32]  Demetrios G. Lainiotis,et al.  Joint Detection, Estimation and System Identification , 1971, Inf. Control..

[33]  V. Walton,et al.  Detecting Instrument Malfunctions in Control Systems , 1975, IEEE Transactions on Aerospace and Electronic Systems.

[34]  Alan S. Willsky,et al.  Failure Detection with Uncertain Models , 1983, 1983 American Control Conference.

[35]  Alan S. Willsky,et al.  A survey of design methods for failure detection in dynamic systems , 1976, Autom..

[36]  Jitendra Tugnait.  Detection and estimation for abruptly changing systems , 1981, CDC 1981.

[37]  Stanley B. Gershwin,et al.  Estimation of Roadway Traffic Density on Freeways Using Presence Detector Data , 1980 .