Open AccessComparative Study of Mamdani-type and Sugeno-type Fuzzy Inference Systems for Coupled Water Tank
Author(s) -
Halim Mudia
Publication year - 2020
Publication title -
indonesian journal of artificial intelligence and data mining
Language(s) - English
Resource type - Journals
eISSN - 2614-6150
pISSN - 2614-3372
DOI - 10.24014/ijaidm.v3i1.9309
Subject(s) - setpoint , adaptive neuro fuzzy inference system , fuzzy control system , defuzzification , fuzzy logic , computer science , neuro fuzzy , fuzzy set operations , control theory (sociology) , artificial intelligence , control engineering , fuzzy number , fuzzy set , engineering , control (management)
The level and flow control in tanks are the heart of all chemical engineering system. The control of liquid level in tanks and flow between tanks is a basic problem in the process industries. Many times the liquids will be processed by chemical or mixing treatment in the tanks, but always the level of fluid in the tanks must be controlled and the flow between tanks must be regulated in presence of non-linearity. Threfore, in this paper will use fuzzy inference systems to control of level 2 are developed using Mamdani-type and Sugeno-type fuzzy models. The outcome obtained by two fuzzy inference systems is evaluated. This paper summarizes the essential variation among the Mamdani-type and Sugeno-type fuzzy inference systems with setpoint of level is 10 centimeter. Matlab fuzzy logic toolbox is used for the simulation of both the models. This also confirms which one is a superior choice of the two fuzzy inference systems to control of level 2 in tank 2. The results show madani-type fuzzy inference system is superior as compared to sugeno-type fuzzy inference system.