Systems identification with genetic algorithms

Genetic algorithms are applied to the identification of black-box systems and partially known systems. The approach is best suited to the partially known systems (PKS) problem; in contrast to least-squares-based algorithms for identification of linear black-box systems, corresponding algorithms for identification of partially known systems are in the early stages of development. The best known algorithms for PKS identification suffer from local minima problems. It is shown that the genetic search and optimisation approach overcomes the local minima problem. Further, the approach is applicable immediately to multiparameter PKS identification problems without modification. This paper outlines a framework for black-box and PKS identification with genetic algorithms