Efficient output solution for nonlinear stochastic optimal control problem with model-reality differences
type: Item
instance of: scholarly article
title: Efficient output solution for nonlinear stochastic optimal control problem with model-reality differences
zbMATH Open document ID: 1394.49027
DOI: 10.1155/2015/659506
author: Sie Long Kek
author: Kok Lay Teo
author: Mohd Ismail Abdul Aziz
published in: Mathematical Problems in Engineering
publication date: 2018-08-27T00:00:00Z
review text: Summary: A computational approach is proposed for solving the discrete time nonlinear stochastic optimal control problem. Our aim is to obtain the optimal output solution of the original optimal control problem through solving the simplified model-based optimal control problem iteratively. In our approach, the adjusted parameters are introduced into the model used such that the differences between the real system and the model used can be computed. Particularly, system optimization and parameter estimation are integrated interactively. On the other hand, the output is measured from the real plant and is fed back into the parameter estimation problem to establish a matching scheme. During the calculation procedure, the iterative solution is updated in order to approximate the true optimal solution of the original optimal control problem despite model-reality differences. For illustration, a wastewater treatment problem is studied and the results show the efficiency of the approach proposed.
Mathematics Subject Classification ID: 49M20
Mathematics Subject Classification ID: 93C55
zbMATH DE Number: 6926930
Wikidata QID: Q59119366
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2015/659506
OpenAlex ID: W2091537628
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description: scientific article; zbMATH DE number 6926930