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Control of the humidity percentage of a bioreactor using a fuzzy controller to grow bonsai
Author(s) -
Jesús de la Cruz-Alejo,
Hugo Beatriz Cuellar,
Irving Cardiel Alcocer Guillermo
Publication year - 2022
Publication title -
international journal of power electronics and drive systems/international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
eISSN - 2722-2578
pISSN - 2722-256X
DOI - 10.11591/ijece.v12i3.pp2465-2476
Subject(s) - controller (irrigation) , propeller , arduino , computer science , fuzzy logic , control theory (sociology) , matlab , humidity , simulation , automotive engineering , control (management) , engineering , embedded system , artificial intelligence , operating system , marine engineering , physics , agronomy , biology , thermodynamics
Different controllers have been designed and used to cultivate bonsai, which need specific conditions to grow and survive in a different place or climate, for this case, humidity. In this work, theoretical, simulation and experimental level are compared and presented in terms of performance characteristics such as complexity, accuracy and convergence of an algorithm proposed to design and implement a fuzzy controller used in a bioreactor to control the humidity percentage to grow bonsai. The MATLAB™ script and fuzzy logic Toolbox™ were used for the analysis and simulation. The controller implementation was done on an Arduino Uno board, and 25850 bytes or 80% of the memory were used to implement it. A sensor to monitor the humidity percentage, a stepper motor connected to a water tap, and a DC motor connected to a propeller were used to adjust the humidity percentage of the bioreactor. The controller results show a maximum error of ±1% for all entire range, and a processing time of 5 milliseconds for one iteration. The results of the tests carried out in the bioreactor are in accordance with the predictions and theoretical simulations, which presents a maximum error of 3%, and a convergence time of 50 seconds for the worst case.

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