Temperature Control of Focused Beam Lamp: PID-Controlled Pulse Width Modulation using MATLAB Simulink and Arduino

This research explores the application of PID control on Arduino Uno using MATLAB Simulink to maintain temperature stability in a system. The main advantage of the PID approach is its adaptability to a variety of temperature control scenarios. Through MATLAB Simulink, users can easily optimize PID parameters such as P, I, and D according to system characteristics and specific needs. The three graphs analyzed depict the system response to changes in PID parameters. The first graph shows a moderate response with controlled fluctuations, reaching setpoint at 60 seconds. The second graph shows a dynamic and complex response, while the third graph produces a very active response with significant fluctuations. The results show that a higher P value results in a more active response and larger fluctuations, but the parameter adjustment must be carried out carefully to achieve a balance between fast response and system stability. In conclusion, the first graph strikes a good balance between responsiveness and stability, while the second and third graphs show the challenges in maintaining stability in certain situations

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Publication Details

Journal
JE-UNISLA
Published
2024-09-05
DOI
https://doi.org/10.30736/je-unisla.v9i2.1223
Primary Topic
Extremum Seeking Control Systems
Type
article
Field-Weighted Citation Impact
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article

Temperature Control of Focused Beam Lamp: PID-Controlled Pulse Width Modulation using MATLAB Simulink and Arduino

Andi Sudjana Putra, Miftahur Rohman, Farid Baskoro, Дмитриков В. Ф
JE-UNISLA
Extremum Seeking Control Systems
article

Temperature Control of Focused Beam Lamp: PID-Controlled Pulse Width Modulation using MATLAB Simulink and Arduino

Andi Sudjana Putra, Miftahur Rohman, Farid Baskoro, Дмитриков В. Ф
article en

Abstract

This research explores the application of PID control on Arduino Uno using MATLAB Simulink to maintain temperature stability in a system. The main advantage of the PID approach is its adaptability to a variety of temperature control scenarios. Through MATLAB Simulink, users can easily optimize PID parameters such as P, I, and D according to system characteristics and specific needs. The three graphs analyzed depict the system response to changes in PID parameters. The first graph shows a moderate response with controlled fluctuations, reaching setpoint at 60 seconds. The second graph shows a dynamic and complex response, while the third graph produces a very active response with significant fluctuations. The results show that a higher P value results in a more active response and larger fluctuations, but the parameter adjustment must be carried out carefully to achieve a balance between fast response and system stability. In conclusion, the first graph strikes a good balance between responsiveness and stability, while the second and third graphs show the challenges in maintaining stability in certain situations

JE-UNISLAVol. 9(2)
Universitas Negeri Surabaya (ID)
Openalex Percentile: Top 67%
Extremum Seeking Control Systems
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