Nonlinear state estimation under bounded noises
Most of the existing nonlinear state estimation methods require to know the statistical information of noises. However, the statistical information may not be accurately obtained or satisfied in practical applications. Actually, the noises are always bounded in a practical system. In this paper, we...
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sg-ntu-dr.10356-1439722020-10-06T01:19:01Z Nonlinear state estimation under bounded noises Chen, Bo Hu, Guoqiang School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Nonlinear Estimation Bounded Noises Most of the existing nonlinear state estimation methods require to know the statistical information of noises. However, the statistical information may not be accurately obtained or satisfied in practical applications. Actually, the noises are always bounded in a practical system. In this paper, we study the nonlinear state estimation problem under bounded noises, where the addressed noises do not provide any statistical information, and the bounds of noises are also unknown. By using matrix analysis and second-order Taylor series expansion, a novel constructive method is proposed to find an upper bound of the square error of the nonlinear estimator. Then, a convex optimization problem on the design of an optimal estimator gain is established in terms of linear matrix inequalities, which can be solved by standard software packages. Moreover, stability conditions are derived such that the square error of the designed nonlinear estimator is asymptotically bounded. Finally, two illustrative examples are employed to show the advantages and effectiveness of the proposed methods. National Research Foundation (NRF) This work was supported in part by the National Research Foundation , Prime Minister’s Office, Singapore under the Energy Innovation Research Programme (EIRP) for Building Energy Efficiency Grant Call, administered by the Building and Construction Authority (NRF2013EWT-EIRP004-051), and in part by the National Natural Science Funds of China under Grant 61673351. The material in this paper was not presented at any conference. This paper was recommended for publication in revised form by Associate Editor Antonio Vicino under the direction of Editor Torsten Söderström. 2020-10-06T01:19:01Z 2020-10-06T01:19:01Z 2018 Journal Article Chen, B., & Hu, G. (2018). Nonlinear state estimation under bounded noises. Automatica, 98, 159-168. doi:10.1016/j.automatica.2018.09.029 0005-1098 https://hdl.handle.net/10356/143972 10.1016/j.automatica.2018.09.029 98 159 168 en Automatica © 2018 Elsevier Ltd. All rights reserved. |
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Engineering::Electrical and electronic engineering Nonlinear Estimation Bounded Noises Chen, Bo Hu, Guoqiang Nonlinear state estimation under bounded noises |
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Most of the existing nonlinear state estimation methods require to know the statistical information of noises. However, the statistical information may not be accurately obtained or satisfied in practical applications. Actually, the noises are always bounded in a practical system. In this paper, we study the nonlinear state estimation problem under bounded noises, where the addressed noises do not provide any statistical information, and the bounds of noises are also unknown. By using matrix analysis and second-order Taylor series expansion, a novel constructive method is proposed to find an upper bound of the square error of the nonlinear estimator. Then, a convex optimization problem on the design of an optimal estimator gain is established in terms of linear matrix inequalities, which can be solved by standard software packages. Moreover, stability conditions are derived such that the square error of the designed nonlinear estimator is asymptotically bounded. Finally, two illustrative examples are employed to show the advantages and effectiveness of the proposed methods. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Chen, Bo Hu, Guoqiang |
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Article |
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Chen, Bo Hu, Guoqiang |
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Chen, Bo |
title |
Nonlinear state estimation under bounded noises |
title_short |
Nonlinear state estimation under bounded noises |
title_full |
Nonlinear state estimation under bounded noises |
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Nonlinear state estimation under bounded noises |
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Nonlinear state estimation under bounded noises |
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nonlinear state estimation under bounded noises |
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2020 |
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https://hdl.handle.net/10356/143972 |
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1681056474911997952 |