EKF-Based Enhanced Performance Controller Design for Nonlinear Stochastic Systems

Yuyang Zhou; Qichun Zhang; Hong Wang; Ping Zhou; Tianyou Chai

doi:10.1109/TAC.2017.2742661

EKF-Based Enhanced Performance Controller Design for Nonlinear Stochastic Systems

Yuyang Zhou, Qichun Zhang, Hong Wang, Ping Zhou, Tianyou Chai

Research output: Contribution to journal › Article › peer-review

65 Scopus citations

Abstract

In this paper, a novel control algorithm is presented to enhance the performance of the tracking property for a class of nonlinear and dynamic stochastic systems subjected to non-Gaussian noises. Although the existing standard PI controller can be used to obtain the basic tracking of the systems, the desired tracking performance of the stochastic systems is difficult to achieve due to the random noises. To improve the tracking performance, an enhanced performance loop is constructed using the EKF-based state estimates without changing the existing closed loop with a PI controller. Meanwhile, the gain of the enhanced performance loop can be obtained based upon the entropy optimization of the tracking error. In addition, the stability of the closed loop system is analyzed in the mean-square sense. The simulation results are given to illustrate the effectiveness of the proposed control algorithm.

Original language	English
Pages (from-to)	1155-1162
Number of pages	8
Journal	IEEE Transactions on Automatic Control
Volume	63
Issue number	4
DOIs	https://doi.org/10.1109/TAC.2017.2742661
State	Published - Apr 2018
Externally published	Yes

Funding

Manuscript received April 16, 2017; revised April 19, 2017 and July 6, 2017; accepted August 7, 2017. Date of publication August 21, 2017; date of current version March 27, 2018. This work was supported in part by the PNNL Control of Complex Systems Initiative and in part by the National Natural Science Foundation of China under Grants 61621004,61573022 and 61333007. Recommended by Associate Editor Zhiwei Gao. (Corresponding author: Yuyang Zhou.) Y. Zhou is with the School of Electrical and Electronic Engineering, University of Manchester, Manchester M13 9PL, U.K. (e-mail: annamada@ 163.com).

Funders	Funder number
U.K.
School of Electronic Engineering and Computer Science
Pacific Northwest National Laboratory
University of Manchester	M13 9PL
National Natural Science Foundation of China	61333007, 61621004,61573022

Keywords

Extended Kalman filter (EKF)
minimum entropy criterion
non-Gaussian stochastic nonlinear systems
tracking performance enhancement

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10.1109/TAC.2017.2742661

Cite this

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title = "EKF-Based Enhanced Performance Controller Design for Nonlinear Stochastic Systems",

abstract = "In this paper, a novel control algorithm is presented to enhance the performance of the tracking property for a class of nonlinear and dynamic stochastic systems subjected to non-Gaussian noises. Although the existing standard PI controller can be used to obtain the basic tracking of the systems, the desired tracking performance of the stochastic systems is difficult to achieve due to the random noises. To improve the tracking performance, an enhanced performance loop is constructed using the EKF-based state estimates without changing the existing closed loop with a PI controller. Meanwhile, the gain of the enhanced performance loop can be obtained based upon the entropy optimization of the tracking error. In addition, the stability of the closed loop system is analyzed in the mean-square sense. The simulation results are given to illustrate the effectiveness of the proposed control algorithm.",

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AU - Zhang, Qichun

AU - Wang, Hong

AU - Zhou, Ping

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PY - 2018/4

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N2 - In this paper, a novel control algorithm is presented to enhance the performance of the tracking property for a class of nonlinear and dynamic stochastic systems subjected to non-Gaussian noises. Although the existing standard PI controller can be used to obtain the basic tracking of the systems, the desired tracking performance of the stochastic systems is difficult to achieve due to the random noises. To improve the tracking performance, an enhanced performance loop is constructed using the EKF-based state estimates without changing the existing closed loop with a PI controller. Meanwhile, the gain of the enhanced performance loop can be obtained based upon the entropy optimization of the tracking error. In addition, the stability of the closed loop system is analyzed in the mean-square sense. The simulation results are given to illustrate the effectiveness of the proposed control algorithm.

AB - In this paper, a novel control algorithm is presented to enhance the performance of the tracking property for a class of nonlinear and dynamic stochastic systems subjected to non-Gaussian noises. Although the existing standard PI controller can be used to obtain the basic tracking of the systems, the desired tracking performance of the stochastic systems is difficult to achieve due to the random noises. To improve the tracking performance, an enhanced performance loop is constructed using the EKF-based state estimates without changing the existing closed loop with a PI controller. Meanwhile, the gain of the enhanced performance loop can be obtained based upon the entropy optimization of the tracking error. In addition, the stability of the closed loop system is analyzed in the mean-square sense. The simulation results are given to illustrate the effectiveness of the proposed control algorithm.

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EKF-Based Enhanced Performance Controller Design for Nonlinear Stochastic Systems

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