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dc.contributor.authorZhou, Yuyangen
dc.contributor.authorZhang, Qichunen
dc.contributor.authorWang Hongen
dc.contributor.authorZhou Pingen
dc.contributor.authorChai, Tianyouen
dc.date.accessioned2017-10-11T11:43:14Z
dc.date.available2017-10-11T11:43:14Z
dc.date.issued2017-08-21
dc.identifier.citationZhou, Y. et al (2017) EKF-based Enhanced Performance Controller Design for Non-linear Stochastic Systems. IEEE Transactions on Automatic Control, PP (99),en
dc.identifier.urihttp://hdl.handle.net/2086/14603
dc.description.abstractIn this paper, a novel control algorithm is presented to enhance the performance of the tracking property for a class of non-linear 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 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 analysed in the mean square sense. The simulation results are given to illustrate the effectiveness of the proposed control algorithm.en
dc.language.isoenen
dc.publisherIEEEen
dc.subjectStochastic systemsen
dc.subjectEntropyen
dc.subjectAlgorithm design and analysisen
dc.subjectKalman filtersen
dc.subjectControl systemsen
dc.subjectProbability density functionen
dc.titleEKF-based Enhanced Performance Controller Design for Non-linear Stochastic Systemsen
dc.typeArticleen
dc.identifier.doihttps://doi.org/10.1109/TAC.2017.2742661
dc.peerreviewedYesen
dc.funderPNNL Control of Complex Systems Initiativeen
dc.funderNational Natural Science Foundation of Chinaen
dc.projectidNational Natural Science Foundation of China under Grant 61621004 and Grant 61333007.en
dc.cclicenceCC-BY-NC-NDen
dc.researchinstituteInstitute of Engineering Sciences (IES)en


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