Ekquential algorithms for prediction, jiltering and smoothing are developed for a class of linear distributed-parameter system. The class of systems concerned is that involving noisy measurement data which are obtained frovn "averaging" and "scanner''-type sensors. Tk basic tools of the development
Joint state and parameter estimation for distributed mechanical systems
β Scribed by Philippe Moireau; Dominique Chapelle; Patrick Le Tallec
- Publisher
- Elsevier Science
- Year
- 2008
- Tongue
- English
- Weight
- 913 KB
- Volume
- 197
- Category
- Article
- ISSN
- 0045-7825
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β¦ Synopsis
We present a novel strategy to perform estimation for a dynamical mechanical system in standard operating conditions, namely, without ad hoc experimental testing. We adopt a sequential approach, and the joint state-parameter estimation procedure is based on a state estimator inspired from collocated feedback control. This type of state estimator is chosen due to its particular effectiveness and robustness, but the methodology proposed to adequately extend state estimation to joint state-parameter estimation is general, and -indeedapplicable with any other choice of state feedback observer. The convergence of the resulting joint estimator is mathematically established. In addition, we demonstrate its effectiveness with a biomechanical test problem defined to feature the same essential characteristics as a heart model, in which we identify localized contractility and stiffness parameters using measurements of a type that is available in medical imaging.
π SIMILAR VOLUMES
Point, N., A. Vande Wouwer, M. Remy and M. Zeitz, PC environment for simulation and parameter estimation of distributed parameter systems, Mathematics and Computers in Simulation 35 (1993) 481-491. ## 1. Introduction Many works in the field of distributed parameter systems have demonstrated that t
## Abstract This paper presents a method which aims at improving parameter estimation in dynamical systems. The general principle of the method is based on a modification of the leastβsquares objective function by means of a weighting operator, in view to improve the conditioning of the identificat