OPTIMIZATION AND CONTROL OF A CONTINUOUS STIRRED TANK FERMENTER USINGLEARNING-SYSTEM

A variable structure learning automaton is used as an optimization and control of a continuous stirred tank fermenter. The algorithm require s no modelling of the process. The use of appropriate learning rules e nables to locate the optimum dilution rate in order to maximize an obj ective cost function. It is shown that a hierarchical structure of aut omata can adapt to environmental changes and can also modify efficient ly the domain of variation of the control variable in order to encompa ss the optimum value.