Rule-base generation via symbiotic evolution for a Mamdani-type fuzzy control system

2002 ◽  
Author(s):  
M. Mahfouf ◽  
M. Jamei ◽  
D.A. Linkens
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Rule Base ◽  
Fuzzy Control System

scholarly journals Fuzzy Control System for Smart Energy Management in Residential Buildings Based on Environmental Data

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 752
Author(s):  
Dimitrios Kontogiannis ◽  
Dimitrios Bargiotas ◽  
Aspassia Daskalopulu
Keyword(s):  
Control System ◽  
Energy Consumption ◽  
Decision Tree ◽  
Fuzzy Control ◽  
Residential Buildings ◽  
Environmental Data ◽  
Weather Data ◽  
Series Data ◽  
Rule Base ◽  
Fuzzy Control System

Modern energy automation solutions and demand response applications rely on load profiles to monitor and manage electricity consumption effectively. The introduction of smart control systems capable of handling additional fuzzy parameters, such as weather data, through machine learning methods, offers valuable insights in an attempt to adjust consumer behavior optimally. Following recent advances in the field of fuzzy control, this study presents the design and implementation of a fuzzy control system that processes environmental data in order to recommend minimum energy consumption values for a residential building. This system follows the forward chaining Mamdani approach and uses decision tree linearization for rule generation. Additionally, a hybrid feature selector is implemented based on XGBoost and decision tree metrics for feature importance. The proposed structure discovers and generates a small set of fuzzy rules that highlights the energy consumption behavior of the building based on time-series data of past operation. The response of the fuzzy system based on sample input data is presented, and the evaluation of its performance shows that the rule base generation is derived with improved accuracy. In addition, an overall smaller set of rules is generated, and the computation is faster compared to the baseline decision tree configuration.

scholarly journals Sistem Cerdas untuk Inovasi Blender Control System Menggunakan Fuzzy Control System dengan Metode Mamdani

2018 ◽  
pp. 115
Author(s):  
Khomarudin Fahuzan ◽  
Uke Ralmugiz
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Fuzzy Inference ◽  
Inference Rule ◽  
Rule Base ◽  
Inference Control ◽  
Fuzzy Control System ◽  
Hardness Level ◽  
A Value ◽  
Time Required

This research aims to establish a control system on blender by using fuzzy control system with mamdani method. In this study, researchers used input in the form of hardness level and volume of fruit to be blend, while the output is blend time (0 to 180 seconds) with assumption of constant blender velocity). Researchers used fuzzy inference control system with Mamdani method with some stages: fuzzification, inference, rule base, and defuzzification. Fuzzification changes the hardness of the fruit and the volume into a value. Inference created fuzzy output using pre-made rules. Defuzzification counted the time it takes to blend into output. Based on the results of the research, the results obtained for the sample of fruit with a level of hardness of 40%, and volume 4 (400 ml), in obtaining the minimum time required to smooth the fruit about 79 seconds. Thus the fuzzy control system can be used as an innovation to make the control system in blender. This system not only applies to blenders only, but also can be applied to other machines using fuzzy control system.

Design and Implementation of a Fuzzy Control System Applied to a 6 × 4 SRG

2021 ◽  
Vol 57 (1) ◽  
pp. 528-536
Author(s):  
Ghunter Paulo Viajante ◽  
Eric Nery Chaves ◽  
Luis Carlos Miranda ◽  
Marcos Antonio A. de Freitas ◽  
Carlos Antunes de Queiroz ◽  
...  
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Fuzzy Control System ◽  
Design And Implementation

scholarly journals A New Online Learned Interval Type-3 Fuzzy Control System for Solar Energy Management Systems

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Zhi LIU ◽  
Ardashir Mohammadzadeh ◽  
Hamza Turabieh ◽  
Majdi Mafarja ◽  
Shahab S. Band ◽  
...  
Keyword(s):  
Control System ◽  
Solar Energy ◽  
Fuzzy Control ◽  
Energy Management ◽  
Management Systems ◽  
Fuzzy Control System ◽  
Energy Management Systems ◽  
Interval Type ◽  
Type 3
Sign in / Sign up

Export Citation Format

Share Document