期刊
APPLIED SOFT COMPUTING
卷 8, 期 1, 页码 392-401出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.asoc.2007.02.004
关键词
H_infty control; multiobjective genetic algorithms; neural networks; optimization; variable complexity modelling
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.
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