Genetic algorithm in the control optimization.
Genetic algorithm (GA) represents an exploratory search mathematical technique, which uses statistical methods of selection. They are named blind search technique as they usually operate without knowledge of the task domain. GA is inspired from the evolutionary features of biological systems. The natural individual selection of offspring that are better adapted will resist in time (3). The pioneer worker in this field was John Holland and the University of Michigan staff from 1975. The beginning study was in natural adaptive process explanation and continues with computed artificial systems developing that exploit the evolution natural principles. A GA technique was applied for a controller parameter optimization that regulates the mean blood pressure. The intelligent system adjusts the anesthetic agent in order to maintain the pressure constant with small variations from a desired set value. This is usually necessary for anesthesia control (mathematical model from 11, 12). Such a system was developed and tested using computer simulations. This paper describes some aspects about the GA mathematical method and finally the results of the controller implementation are presented.
Boiculese
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Department of Computer Science, Faculty of Medicine, University of Medicine and Pharmacy Gr. T. Popa, Iaşi.
D000465:Algorithms; D000818:Animals; D007446:Chromosome Inversion; D002875:Chromosomes / Q000235:genetics; D002877:Chromosomes, Human / Q000235:genetics; D003198:Computer Simulation; D003433:Crosses, Genetic; D017143:Fuzzy Logic; D006801:Humans; D008957:Models, Genetic; D009154:Mutation / Q000235:genetics; D012098:Reproduction / Q000235:genetics