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dc.contributor.authorKek, S.
dc.contributor.authorTeo, Kok Lay
dc.contributor.authorIsmail, A.
dc.date.accessioned2017-01-30T13:02:11Z
dc.date.available2017-01-30T13:02:11Z
dc.date.created2011-03-02T20:01:35Z
dc.date.issued2010
dc.identifier.citationKek, Sie Long and Teo, Kok Lay and Ismail, A.A. Mohd. 2010. An integrated optimal control algorithm for discrete-time nonlinear stochastic system. International Journal of Control. 83 (12): pp. 2536-2545.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/27941
dc.identifier.doi10.1080/00207179.2010.531766
dc.description.abstract

Consider a discrete-time nonlinear system with random disturbances appearing in the real plant and the output channel where the randomly perturbed output is measurable. An iterative procedure based on the linear quadratic Gaussian optimal control model is developed for solving the optimal control of this stochastic system. The optimal state estimate provided by Kalman filtering theory and the optimal control law obtained from the linear quadratic regulator problem are then integrated into the dynamic integrated system optimisation and parameter estimation algorithm. The iterative solutions of the optimal control problem for the model obtained converge to the solution of the original optimal control problem of the discrete-time nonlinear system, despite model-reality differences, when the convergence is achieved. An illustrative example is solved using the method proposed. The results obtained show the effectiveness of the algorithm proposed.

dc.publisherTaylor & Francis
dc.subjectmodel-reality differences
dc.subjectoptimal control
dc.subjectiterative algorithm
dc.subjectdiscrete-time nonlinear stochastic system
dc.subjectKalman filtering
dc.titleAn integrated optimal control algorithm for discrete-time nonlinear stochastic system
dc.typeJournal Article
dcterms.source.volume83
dcterms.source.startPage2536
dcterms.source.endPage2545
dcterms.source.issn00207179
dcterms.source.titleInternational Journal of Control
curtin.departmentDepartment of Mathematics and Statistics
curtin.accessStatusFulltext not available


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