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dc.contributor.authorZhang, Qichunen
dc.contributor.authorHu, Liangen
dc.date.accessioned2018-11-08T11:16:29Z
dc.date.available2018-11-08T11:16:29Z
dc.date.issued2018-11-01
dc.identifier.citationZhang, Q. and Hu, L. (2018) Probabilistic Decoupling Control for Stochastic Non-Linear Systems Using EKF-Based Dynamic Set-Point Adjustment. 2018 UKACC 12th International Conference on Control (CONTROL), Sheffield, United Kingdom, 2018, pp. 330-335.en
dc.identifier.urihttp://hdl.handle.net/2086/17115
dc.description.abstractIn this paper, a novel decoupling control scheme is presented for a class of stochastic non-linear systems by estimation-based dynamic set-point adjustment. The loop control layer is designed using PID controller where the parameters are fixed once the design procedure is completed, which can be considered as an existing control loop. While the compensator is designed to achieve output decoupling in probability sense by a set-point adjustment approach based on the estimated states of the systems using extended Kalman filter. Based upon the mutual information of the system outputs, the parameters of the set-point adjustment compensator can be optimised. Using this presented control scheme, the analysis of stability is given where the tracking errors of the closed-loop systems are bounded in probability one. To illustrate the effectiveness of the presented control scheme, one numerical example is given and the results show that the systems are stable and the probabilistic decoupling is achieved simultaneously.en
dc.language.isoenen
dc.publisher2018 UKACC 12th International Conference on Control (CONTROL)en
dc.titleProbabilistic Decoupling Control for Stochastic Non-Linear Systems Using EKF-Based Dynamic Set-Point Adjustmenten
dc.typeConferenceen
dc.identifier.doihttps://dx.doi.org/10.1109/CONTROL.2018.8516784
dc.researchgroupInstitute of Engineering Sciences (IES)en
dc.peerreviewedYesen
dc.funderN/Aen
dc.projectidN/Aen
dc.cclicenceCC-BY-NCen
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en
dc.researchinstituteInstitute of Engineering Sciences (IES)en


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