Cart (Loading....) | Create Account
Close category search window

Self-tuning Fuzzy Logic Control of Greenhouse Temperature using Real-coded Genetic Algorithm

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

The purchase and pricing options are temporarily unavailable. Please try again later.
4 Author(s)
Fang Xu ; Mech. Manuf. & Autom., Zhejiang Univ. of Technol., Hangzhou ; Jiaoliao Chen ; Libin Zhang ; Hongwu Zhan

The greenhouse temperature model is built based on the balance of the energy. A new real-coded genetic algorithm (GA) for self-tuning fuzzy logic control (FLC) of greenhouse temperature is proposed, in which, an arithmetical crossover operator, a ranking-based reproduction operator and a non-uniform mutation operator are adopted. The Gaussian input membership functions for the error and the change-in-error of the temperature of FLC is optimized by GA in terms of the root-mean-square error (RMSE) with setpoint and input energy. Compared with the basic fuzzy control, the tuned FLC gives better performance in terms of improving control precision and saving energy

Published in:

Control, Automation, Robotics and Vision, 2006. ICARCV '06. 9th International Conference on

Date of Conference:

5-8 Dec. 2006

Need Help?

IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.