Journal ArticleDOI
Strong tracking filtering of nonlinear time-varying stochastic systems with coloured noise: application to parameter estimation and empirical robustness analysis
D. H. Zhou,Paul M. Frank +1 more
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TLDR
In this paper, Zhou et al. extended the strong tracking filter (STF) for nonlinear systems with white noise to a class of nonlinear time-varying stochastic systems with coloured noise.Abstract:
The strong tracking filter (STF) proposed by Zhou et al. in 1992, which was developed for nonlinear systems with white noise, is extended to a class of nonlinear time-varying stochastic systems with coloured noise. A new concept of‘softening factor’is introduced to make the state estimator much smoother; its value can be preselected by computer simulations via a heuristic searching scheme. The STF is then used to estimate the parameters of a class of nonlinear time-varying stochastic systems in the presence of coloured noise. The robustness against model uncertainty of the STF is thoroughly studied via Monte Carlo simulations. The results show that the STF has strong robustness against model-plant parameter mismatches in the statistics of the initial conditions, the statistics of the process noise and the measurement noise, the system parameters, and the parameters in the measurement noise model. To a great extent the STF can give bias-free parameter estimations, where the parameters may be randomly time ...read more
Citations
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References
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Journal Article
Optimal Filtering
TL;DR: This book helps to fill the void in the market and does that in a superb manner by covering the standard topics such as Kalman filtering, innovations processes, smoothing, and adaptive and nonlinear estimation.
Journal ArticleDOI
Fault diagnosis in dynamic systems using analytical and knowledge-based redundancy—a survey and some new results
TL;DR: In this article, the authors review the state of the art of fault detection and isolation in automatic processes using analytical redundancy, and present some new results with emphasis on the latest attempts to achieve robustness with respect to modelling errors.
Journal ArticleDOI
Process fault detection based on modeling and estimation methods-A survey
TL;DR: This contribution presents a brief summary of some basic fault detection methods, followed by a description of suitable parameter estimation methods for continuous-time models.
Journal ArticleDOI
Asymptotic behavior of the extended Kalman filter as a parameter estimator for linear systems
TL;DR: In this paper, a convergence analysis of the extended Kalman filter for nonlinear systems with unknown parameters is given, and it is shown that in general the estimates may be biased or divergent and the causes for this are displayed.