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Output regulation for discrete-time nonlinear stochastic optimal control problems with model-reality differences

Kek, Sie Long and Abd. Aziz, Mohd. Ismail (2015) Output regulation for discrete-time nonlinear stochastic optimal control problems with model-reality differences. Numerical Algebra, Control And Optimization, 5 (3). pp. 275-288. ISSN 2151-0032

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Official URL: http://dx.doi.org/10.3934/naco.2015.3.275


In this paper, we propose an output regulation approach, which is based on principle of model-reality differences, to obtain the optimal output measurement of a discrete-time nonlinear stochastic optimal control problem. In our approach, a model-based optimal control problem with adding the ad- justable parameters is considered. We aim to regulate the optimal output trajectory of the model used as closely as possible to the output measurement of the original optimal control problem. In doing so, an expanded optimal control problem is introduced, where system optimization and parameter es- timation are integrated. During the computation procedure, the differences between the real plant and the model used are measured repeatedly. In such a way, the optimal solution of the model is updated. At the end of iteration, the converged solution approaches closely to the true optimal solution of the original optimal control problem in spite of model-reality differences. It is im- portant to notice that the resulting algorithm could give the output residual that is superior to those obtained from Kalman filtering theory. The accuracy of the output regulation is therefore highly recommended. For illustration, a continuous stirred-tank reactor problem is studied. The results obtained show the efficiency of the approach proposed.

Item Type:Article
Uncontrolled Keywords:adjustable parameters, iterative algorithm, model-reality differences, output regulation, stochastic optimal control
Subjects:A General Works
ID Code:58740
Deposited By: Haliza Zainal
Deposited On:04 Dec 2016 12:07
Last Modified:03 May 2017 08:59

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