{"title":"Local E-optimality Conditions for Trajectory Design to Estimate Parameters in Nonlinear Systems.","authors":"Andrew D Wilson, Todd D Murphey","doi":"10.1109/ACC.2014.6858649","DOIUrl":null,"url":null,"abstract":"<p><p>This paper develops an optimization method to synthesize trajectories for use in the identification of system parameters. Using widely studied techniques to compute Fisher information based on observations of nonlinear dynamical systems, an infinite-dimensional, projection-based optimization algorithm is formulated to optimize the system trajectory using eigenvalues of the Fisher information matrix as the cost metric. An example of a cart-pendulum simulation demonstrates a significant increase in the Fisher information using the optimized trajectory with decreased parameter variances shown through Monte-Carlo tests and computation of the Cramer-Rao lower bound.</p>","PeriodicalId":74510,"journal":{"name":"Proceedings of the ... American Control Conference. American Control Conference","volume":"2014 ","pages":"443-450"},"PeriodicalIF":0.0000,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/ACC.2014.6858649","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the ... American Control Conference. American Control Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACC.2014.6858649","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
This paper develops an optimization method to synthesize trajectories for use in the identification of system parameters. Using widely studied techniques to compute Fisher information based on observations of nonlinear dynamical systems, an infinite-dimensional, projection-based optimization algorithm is formulated to optimize the system trajectory using eigenvalues of the Fisher information matrix as the cost metric. An example of a cart-pendulum simulation demonstrates a significant increase in the Fisher information using the optimized trajectory with decreased parameter variances shown through Monte-Carlo tests and computation of the Cramer-Rao lower bound.
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