Education, Science, Technology, Innovation and Life
Open Access
Sign In
  1. Home
  2. Journals
  3. Advances in Computer, Signals and Systems
  4. Vol 7, Issue 4, 2023

Construction of Intelligent Temperature Control System Based on STM32 Single-chip Microcomputer

Download as PDF

DOI: 10.23977/acss.2023.070401 | Downloads: 25 | Views: 192

Author(s)

Yao Ying 1

Affiliation(s)

1 School of Electrical and Automation Engineering, Liaoning Institute of Science and Technology, Benxi, Liaoning, 117004, China

Corresponding Author

Yao Ying

ABSTRACT

Temperature is a very common and important parameter in manufacturing processes and scientific research experiments. In order to conduct production efficiently and achieve the desired control effect, important parameters such as temperature, power, pressure, and speed must be effectively controlled during production or scientific experiments. The purpose of this article was to study the construction of an intelligent temperature control system based on the STM32 single-chip microcomputer. This article discussed the control of the surface temperature of the heating roller during the fixing operation of the copier. The main research content was the application of STM32 single-chip microcomputer in temperature control. Firstly, the advantages of STM32 single-chip microcomputer were described, and the fuzzy PID (Proportional Integral Derivative) control strategy was applied to temperature control, thus realizing the fuzzy PID control algorithm. Finally, the entire temperature control system was integrated into a complete copier, and the traditional PID control algorithm was compared with the fuzzy PID control algorithm. The results showed that the temperature control system using the fuzzy PID control algorithm had good stability, and its accuracy could be maintained within ±3 degrees Celsius.

KEYWORDS

STM32 Single-chip Microcomputer, Intelligent Temperature Control, System Construction, Fuzzy PID Control

CITE THIS PAPER

Yao Ying. Construction of Intelligent Temperature Control System Based on STM32 Single-chip Microcomputer. Advances in Computer, Signals and Systems (2023) Vol. 7: 1-10. DOI: http://dx.doi.org/10.23977/acss.2023.070401.

REFERENCES

[1] Blaise Ravelo, Mathieu Guerin, Wenceslas Rahajandraibe, Valentin Gies, Lala H. Rajaoarisoa, Sebastien Lallechere. (2022) Low-Pass NGD Numerical Function and STM32 MCU Emulation Test. IEEE Trans. Ind. Electron. 69(8): 8346-8355 
[2] Cong Zhang, Zhisheng Wang, Dan Zhu, Haiwen Gao, Nianyu Zou. (2021) A lighting control system of art museum based on image recognition and STM32. Int. J. Sens. Networks 37(2): 112-124 
[3] Patryk Chaber, Maciej Lawrynczuk. (2019) Fast Analytical Model Predictive Controllers and Their Implementation for STM32 ARM Microcontroller. IEEE Trans. Ind. Informatics 15(8): 4580-4590 
[4] Parvesh Saini, Padmanabh Thakur. (2022) H-Infinity Based Robust Temperature Controller Design for a Non-linear Systems. Wirel. Pers. Commun. 126(1): 305-333 
[5] Vishal Vishnoi, Sheela Tiwari, Rajesh Kumar Singla. (2021) Controller Design for Temperature Control of MISO Water Tank System: Simulation Studies. Int. J. Cogn. Informatics Nat. Intell. 15(4): 1-13 
[6] Michiel A. J. uit het Broek, Gerlach Van der Heide, Nicky D. van Foreest. (2020) Energy-saving policies for temperature-controlled production systems with state-dependent setup times and costs. Eur. J. Oper. Res. 287(3): 916-928 
[7] Syed Usman Amin, Muhammad Aaquib Shahbaz, Syed Arsalan Jawed, Fahd Khan, Muhammad Junaid, Danish Kaleem, Musaddiq Siddiq, Zain Hussain Warsi, Naveed. (2022) Temperature and Humidity Controlled Test Bench for Temperature Sensor Characterization. J. Electron. Test. 38(4): 453-461 
[8] Mihaela Popa, Daniel Alexuta, Valentina Emilia Balas. (2022) Fuzzy-interpolative control of temperatures for the intelligent rooftop greenhouse. J. Intell. Fuzzy Syst. 43(2): 1793-1797 
[9] Vincent Taboga, Amine Bellahsen, Hanane Dagdougui. (2022) An Enhanced Adaptivity of Reinforcement Learning-Based Temperature Control in Buildings Using Generalized Training. IEEE Trans. Emerg. Top. Comput. Intell. 6(2): 255-266 
[10] Ganapati Bhat, Suat Gumussoy, Umit Y. Ogras. (2021) Analysis and Control of Power-Temperature Dynamics in Heterogeneous Multiprocessors. IEEE Trans. Control. Syst. Technol. 29(1): 329-341 
[11] Stefano Marelli, Matteo Corno. (2021) Model-Based Estimation of Lithium Concentrations and Temperature in Batteries Using Soft-Constrained Dual Unscented Kalman Filtering. IEEE Trans. Control. Syst. Technol. 29(2): 926-933 
[12] Haocong Cai, Zhigang Wu, Min Chen. (2023) Design of STM32-based Quadrotor UAV Control System. KSII Trans. Internet Inf. Syst. 17(2): 353-368 
[13] Xiaochun Guan, Sheng Lou, Han Li, Tinglong Tang. (2021) Intelligent control of quad-rotor aircrafts with a STM32 microcontroller using deep neural networks. Ind. Robot 48(5): 700-709 
[14] Hung Guo, Evgeni Magid, Kuo-Hsien Hsia, Kuo-Lan Su. (2021) Development of IoT Module with AI Function Using STM32 Chip. J. Robotics Netw. Artif. Life 7(4): 253-257 
[15] Qian Zhang, Tengjin Zhao, Zhiyue Zhang. (2020) Unfitted finite element for optimal control problem of the temperature in composite media with contact resistance. Numer. Algorithms 84(1): 165-180 
[16] R. Vijay Aravind, P. Balasubramaniam. (2023) Membership-Function-Dependent Design of Quantized Fuzzy Sampled-Data Controller for Semi-Markovian Jump Systems With Actuator Faults. IEEE Trans. Fuzzy Syst. 31(1): 40-52 
[17] Ankur Rai, Dushmanta Kumar Das. (2022) Ennoble class topper optimization algorithm based fuzzy PI-PD controller for micro-grid. Appl. Intell. 52(6): 6623-6645 
[18] F. Vijay Amirtha Raj, V. Kamatchi Kannan. (2022) Particle Swarm Optimized Deep Convolutional Neural Sugeno-Takagi Fuzzy PID Controller in Permanent Magnet Synchronous Motor. Int. J. Fuzzy Syst. 24(1): 180-201 
[19] Mohamed Barakat. (2022) Optimal design of fuzzy-PID controller for automatic generation control of multi-source interconnected power system. Neural Comput. Appl. 34(21): 18859-18880 
[20] Ritu Raj, B. M. Mohan, Dong-Eun Lee, Jung-Min Yang. (2022) Derivation and structural analysis of a three-input interval type-2 TS fuzzy PID controller. Soft Comput. 26(2): 589-603

Subscription
E-Mail Alert
Most popular papers
Call for Special Issue
Publication Ethics & OA Statement
Plagiarism Policy
Contact Us
Downloads: 5496
Visits: 159734

Sponsors, Associates, and Links

All published work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright © 2016 - 2031 Clausius Scientific Press Inc. All Rights Reserved.