Multiobjective optimization using variable complexity modelling for control system design

doi:10.1016/j.asoc.2007.02.004

2008-01-01

PRE

P.J. Fleming

Ryuichi Yokoyama

DOI：10.1016/j.asoc.2007.02.004

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摘要

En 中文

A multi-stage design approach that uses a multiobjective genetic algorithm as the framework for optimization and multiobjective preference articulation, and an H_infty loop-shaping technique are used to design controllers for a gas turbine engine. A non-linear model is used to assess performance of the controller. Because the computational load of applying multiobjective genetic algorithm to this control strategy is very high, a neural network and response surface models are used in order to speed up the design process within the framework of a multiobjective genetic algorithm. The final designs are checked using the original non-linear model. (C) 2007 Elsevier B. V. All rights reserved.

Keyword:

H_infty control

multiobjective genetic algorithms

neural networks

optimization

variable complexity modelling