A Project-Based Design of a Two-Wheeled Self-Balancing Robot Using PID Controller
Authors
Faculty of Electronics and Computer Technology and Engineering, Universiti Teknikal Malaysia Melaka (UTeM), 76100 Durian Tunggal, Melaka, Malaysia (Malaysia)
Faculty of Electronics and Computer Technology and Engineering, Universiti Teknikal Malaysia Melaka (UTeM), 76100 Durian Tunggal, Melaka, Malaysia (Malaysia)
Article Information
DOI: 10.47772/IJRISS.2026.100500314
Subject Category: Science Education
Volume/Issue: 10/5 | Page No: 4617-4623
Publication Timeline
Submitted: 2026-05-07
Accepted: 2026-05-12
Published: 2026-05-30
Abstract
This project focuses on the design and development of a two-wheel self-balancing robot prototype controlled by a PID algorithm. The hardware setup includes an ESP32 microcontroller that processes orientation data from an MPU6050 sensor to manage the movement of NEMA17 stepper motors. A key feature of this system is its connectivity; sensor data is sent to the Blynk IoT platform, which allows for remote PID tuning and system adjustments without needing to modify the code manually. At the same time, the data is exported to MATLAB for a more technical and detailed analysis of the control response. By using a closed-loop control system, the robot can maintain its balance and follow a specific trajectory more effectively, even when faced with external disturbances or changes in the PID parameters. After testing the robot's performance under various settings, the results show a successful implementation of stable control. For future development, adding a camera system could expand the robot's capabilities to include surveillance and monitoring tasks.
Keywords
PID Controller, Self-Balancing Robot, ESP32, MPU6050 Sensor, IoT Monitoring
Downloads
References
1. Baltes, J., Christmann, G., & Saeedvand, S. (2023). A deep reinforcement learning algorithm to control a two-wheeled scooter with a humanoid robot. Engineering Applications of Artificial Intelligence, 126(4), 106941. https://doi.org/10.1016/j.engappai.2023.106941 [Google Scholar] [Crossref]
2. Darko, H., Tone, L., Mitja, T., & Oto, T. (2023). Design and Implementation of ESP32-Based IoT Devices. Sensors 2023, 23(15), 6739. https://doi.org/10.3390/s23156739 [Google Scholar] [Crossref]
3. Emrah, A., Kazim, Y., & Eyup, E. (2021). Use of PID control during education in reinforcement learning on Two Wheel balance robot. Journal of Science PART C: DESIGN AND TECHNOLOGY, 9(4), 597-607. https://doi.org/10.29109/gujsc.955562 [Google Scholar] [Crossref]
4. Hao, L., & Sitjongsataporn, S. (2026). Design and implement of smart voice controlled two-wheeled self-balancer for following and avoidance. International Electrical Engineering Transactions, 11(2). https://ph04.tci-thaijo.org/index.php/IEET/article/view/11634 [Google Scholar] [Crossref]
5. John, A.M. (2023). Modeling and control strategies for a two-wheel balancing mobile robot. Master Thesis, University of Arkansas. https://scholarworks.uark.edu/cgi/viewcontent.cgi?article=6514&context=etd [Google Scholar] [Crossref]
7. Kishore, R., & Rohit, L. (2025). Two wheeled path following self balancing robot. Indian Institute of Technology Delhi. [Google Scholar] [Crossref]
8. https://web.iitd.ac.in/~subashish/ELP7100/Biwheeled_Robot_Rohit_Kishore_Report.pdf [Google Scholar] [Crossref]
9. Maciej, S., & Izabela, K. (2025). Influence of control system architecture on mobile robot stability and performance. Sensors 2025, 25, 7353. https://doi.org/10.3390/s25237353 [Google Scholar] [Crossref]
10. Maheshbhai, V.A., Kumar, D., & Sinha, R. (2020). Development of Two Wheeled Robot (TWR) by Single Stepper Driver using PID controller. Research Square, 1-33. https://doi.org/10.21203/rs.3.rs-56271/v1 [Google Scholar] [Crossref]
11. Nikita, T., & Prajwal, K.T. (2021). PID Controller Based Two Wheeled Self Balancing Robot. 2021 5th International Conference on Trends in Electronics and Informatics. https://doi.org/10.1109/ICOEI51242.2021.9453091 [Google Scholar] [Crossref]
12. Sandeep, G., Kanad R., & Shamim, K. (2025). Self-balancing mobile robot with Bluetooth control: Design, implementation, and performance analysis. Automation, 6(3), 42. https://doi.org/10.3390/automation6030042 [Google Scholar] [Crossref]
13. Tun, H.M., Nwe, M.S., Naing, Z.M., Latt, M.M., Pradhan, D., & Sahu, P.K. (2022). Research on Self-balancing Two Wheels Mobile Robot Control System Analysis. Electrical Science & Engineering, 4(1), 1-7. https://doi.org/10.30564/ese.v4i1.4398 [Google Scholar] [Crossref]
14. Zhang, H., & Nor, N. M. (2025). Control strategies for two-wheeled self-balancing robotic systems: A comprehensive review. Robotics, 14(8), 101. https://doi.org/10.3390/robotics14080101 [Google Scholar] [Crossref]
Metrics
Views & Downloads
Similar Articles
- Exploring the Moderating Role of Demographic Variables in the Relationship Between Scientific Curiosity and Creativity Among Secondary School Students
- Development of a CODE-Based Teaching Guide on the Central Dogma in Biochemistry: A Study in the Philippines
- Scaffolding Genetics Learning in Resource-Constrained Classrooms: Effects of Inquiry-Based Worksheets on Student Achievement
- Chronological Versus Biological Age: The Role of Diet and Healthy Lifestyle in Modulating Epigenetic Aging
- Exploring Relationship Between Reaction Time and Academic Achievement in Science Subjects of Middle Stage Students