Accelerating multi-objective control system design using a neuro-genetic approach

Duarte, N. M.; Ruano, Antonio; Fonseca, C. M.; Fleming, P. J.

http://hdl.handle.net/10400.1/2162

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Abstract(s)

Designing control systems using multiobjective genetic algorithms can lead to a substantial computational load as a result of the repeated evaluation of the multiple objectives and the population-based nature of the search. Here, a neural network approach, based on radial basis functions, is introduced to alleviate this problem by providing computationally inexpensive estimates of objective values during the search. A straightforward example demonstrates the utility of the approach.

Keywords

Mmultiobjective optimisation Genetic algorithms Computer-aided control system design

URI

http://hdl.handle.net/10400.1/2162

Citation

Duarte, N. M.; Ruano, A. E.; Fonseca, C. M.; Fleming, P. J. Accelerating multi-objective control system design using a neuro-genetic approach, Trabalho apresentado em 2000 Congress on Evolutionary Computation, In Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512), La Jolla, CA, USA, 2000.