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Proceedings of the 18th IFAC World Congress

DOI: 10.3182/20110828-6-it-1002.03722

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Input Design for Nonlinear Stochastic Dynamic Systems-A Particle Filter Approach

Journal article published in 2011 by R. Bhushan, R. Bhushan Gopaluni, Thomas B. Schön ORCID, Adrian G. Wills, Gopaluni Bhushan
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

We propose an algorithm for optimal input design in nonlinear stochastic dynamic systems. The approach relies on minimizing a function of the covariance of the parameter estimates of the system with respect to the input. The covariance matrix is approximated using a joint likelihood function of hidden states and measurements, and a combination of state filters and smoothers. The input is parametrized using an autoregressive model. The proposed approach is illustrated through a simulation example.