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A Gauss-Newton Approach for Nonlinear Optimal Control Problem with Model-Reality Differences

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成果类型:
期刊论文
论文标题(中文):
A Gauss-Newton Approach for Nonlinear Optimal Control Problem with Model-Reality Differences
作者:
Sie Long Kek;Jiao Li;Wah June Leong;Mohd Ismail Abd Aziz;PDF
作者机构:
[Sie Long Kek] Center for Research on Computational Mathematics, Universiti Tun Hussein Onn Malaysia, Batu Pahat, Malaysia
[Jiao Li] School of Mathematics and Computing Science, Changsha University of Science and Technology, Changsha, China
[Wah June Leong] Department of Mathematics, Universiti Putra Malaysia, Serdang, Malaysia
[Mohd Ismail Abd Aziz] Department of Mathematical Sciences, Universiti Teknologi Malaysia, Skudai, Malaysia
语种:
英文
关键词:
NONLINEAR;Optimal;Control;Gauss-Newton;APPROACH;ITERATIVE;Procedure;Output;Error;Model-Reality;DIFFERENCES;Gauss-Newton Approach;Iterative Procedure;Output Error;Model-Reality Differences
期刊:
最优化(英文)
ISSN:
2325-7105
年:
2017
卷:
06
期:
03
页码:
85-100
机构署名:
本校为第一机构
院系归属:
数学与统计学院
摘要:
Output measurement for nonlinear optimal control problems is an interesting issue. Because the structure of the real plant is complex, the output channel could give a significant response corresponding to the real plant. In this paper, a least squares scheme, which is based on the Gauss-Newton algorithm, is proposed. The aim is to approximate the output that is measured from the real plant. In doing so, an appropriate output measurement from the model used is suggested. During the computation procedure, the control trajectory is updated iteratively by using the Gauss-Newton recursion scheme. C...

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