Parameter Tuning via Genetic Algorithm of Fuzzy Controller for Fire Tube Boiler | Zendy

Osama Hassanein | Zendy; Ayman A. Aly | Zendy; Ahmed Abo-Ismail | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Parameter Tuning via Genetic Algorithm of Fuzzy Controller for Fire Tube Boiler

Author(s) -

Osama Hassanein,

Ayman A. Aly,

Ahmed Abo-Ismail

Publication year - 2012

Publication title -

international journal of intelligent systems and applications

Language(s) - English

Resource type - Journals

eISSN - 2074-9058

pISSN - 2074-904X

DOI - 10.5815/ijisa.2012.04.02

Subject(s) - boiler (water heating) , computer science , control theory (sociology) , fuzzy logic , genetic algorithm , fuzzy control system , scaling , boiler water , control (management) , mathematics , artificial intelligence , engineering , machine learning , waste management , geometry

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 genetic- fuzzy 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.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research