Parameter Tuning via Genetic Algorithm of Fuzzy Controller for Fire Tube Boiler
نویسندگان
چکیده
The optimal use of fuel energy and water in a fire tube boiler is important in achieving economical system operation, precise control system design required to achieve high speed of response with no overshot. Two artificial intelligence techniques, fuzzy control (FLC) and geneticfuzzy control (GFLC) applied to control both of the water/steam temperature and water level control loops of boiler. The parameters of the FLC are optimized to locating the optimal solutions to meet the required performance objectives using a genetic algorithm. The parameters subject to optimization are the width of the membership functions and scaling factors. The performance of the fire tube boiler that fitted with GFLC has reliable dynamic performance as compared with the system fitted with FLC.
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