Genetic Algorithms for simultaneous identification of local operating regimes and local controller network design

This paper introduces a new genetic algorithm technique for simultaneously finding the local operating regimes and designing local controllers (LCs) for an unknown plant. This is in contrast to previous approaches, where design of LCs in a local controller network (LCN) required a priori knowledge of the plant operating regions. A neural network (NN) model of an experimental nonlinear pH neutralisation process is used to illustrate the potential of the proposed LCN control scheme and confirms that the resulting local controllers act at the same operating points as indicated by an earlier local model network (LMN) representation.

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