Robust filtering for joint state parameter estimation for distributed mechanical systems

Abstract : We present an effective filtering procedure for jointly estimating state variables and parameters in a distributed mechanical system. This method is based on a robust, low-cost filter related to collocated feedback and used to estimate state variables, and an $H^\infty$ setting is then employed to formulate a joint state-parameter estimation filter. In addition to providing a tractable filtering approach for an infinite-dimensional mechanical system, the $H^\infty$ setting allows to consider measurement errors that cannot be handled by Kalman type filters, e.g. for measurements only available on the boundary. For this estimation strategy a complete error analysis is given, and a detailed numerical assessment - using a test problem inspired from cardiac biomechanics - demonstrates the effectiveness of our approach.
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Discrete and Continuous Dynamical Systems - Series A, American Institute of Mathematical Sciences, 2009, 23 (1-2), pp.65-84. 〈10.3934/dcds.2009.23.65〉
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Dominique Chapelle, Philippe Moireau, Patrick Le Tallec. Robust filtering for joint state parameter estimation for distributed mechanical systems. Discrete and Continuous Dynamical Systems - Series A, American Institute of Mathematical Sciences, 2009, 23 (1-2), pp.65-84. 〈10.3934/dcds.2009.23.65〉. 〈hal-00358910〉

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