Input design for detection of abrupt changes in dynamical systems

DOI10.1080/00207179408923118zbMath0808.93063OpenAlexW2065248898MaRDI QIDQ4296441

Martin B. Zarrop, Feza Kerestecioğlu

Publication date: 9 March 1995

Published in: International Journal of Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207179408923118

zbMATH Keywords

input designmultiple hypotheses testsdetection performancecumulative sum test

Mathematics Subject Classification ID

Estimation and detection in stochastic control theory (93E10)

Related Items (12)

Auxiliary signal design for rapid multi-model identification using optimization ⋮ Optimal input design for the detection of changes towards unknown hypotheses ⋮ Detection signal design for failure detection: a robust approach ⋮ Input design for discrimination between classes of LTI models ⋮ Effects of feedback on active fault detection ⋮ On the detection of small parameter variations in linear uncertain systems ⋮ Auxiliary signal design for active failure detection in uncertain linear systems with a priori information ⋮ Active Fault Diagnosis Based on Stochastic Tests ⋮ Optimal piecewise-constant signal design for active fault detection ⋮ A multi-model approach to failure detection in uncertain sampled-data systems ⋮ An active approach for detection of incipient faults ⋮ A model-based approach to fault-tolerant control

Cites Work

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• Process fault detection based on modeling and estimation methods - a survey
• Control, identification, and input optimization
• Detection of abrupt changes in signals and dynamical systems. (Proceedings of a Conference on Detection of Abrupt Changes in Signals and Dynamical Systems, Paris, March 21-22, 1984)
• A survey of design methods for failure detection in dynamic systems
• Optimal input design for autoregressive model discrimination with constrained output variance
• A sequential multiple hypotheses test for the unknown parameters of a Gaussian distribution (Corresp.)
• Procedures for Reacting to a Change in Distribution
• A Sequential Decision Procedure for Choosing One of Three Hypotheses Concerning the Unknown Mean of a Normal Distribution

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