Comparative Analysis of PID Tuning Methods for Speed Control in Mecanum-Wheel Electric Wheelchairs

Authors

  • Nuntachai Thongpance Rangsit University
  • Phichitphon Chotikunnan Rangsit University
  • Anantasak Wongkamhang Rangsit University
  • Rawiphon Chotikunnan Rangsit University
  • Pariwat Imura Rangsit University
  • Wanida Khotakham Rangsit University
  • Anuchit Nirapai Rangsit University
  • Kittipan Roongprasert Rangsit University

DOI:

https://doi.org/10.12928/biste.v7i2.13046

Keywords:

PID Tuning, Cohen-Coon Method, Particle Swarm Optimization (PSO), Assistive Robotics, Embedded Control Systems

Abstract

This study compares two PID controller tuning methods, particle swarm optimization (PSO) and Cohen-Coon, employed for speed control of an omnidirectional Mecanum-wheel electric wheelchair. Mecanum wheels improve maneuverability on powered mobility platforms; yet, controlling these systems is difficult due to nonlinearities and directional coupling effects. This work investigates the effectiveness of PSO as a sophisticated alternative to traditional PID tuning methods, effectively tackling this issue. This study evaluates P, PI, PD, and PID controllers tuned by both Cohen-Coon and PSO methods, applied to a DC motor system simulating real-world wheelchair actuation. Step response-based system identification models the motor using MATLAB/Simulink. Simulations of a 12V DC motor are examined using controlled-step time-domain inputs. Every controller configuration is subjected to evaluation for overshoot, root mean square error (RMSE), rise time, and settling time. The PSO-tuned PID controller exhibited enhanced performance, characterized by a rise time of 2.06 s, a settling time of 2.37 s, an overshoot of 0.78%, and an RMSE of 4.59, far surpassing the Cohen-Coon variant, which had a settling time of 6.12 s and an overshoot of 20.14%. The results indicate that PSO enhances both transient and steady-state performance in intricate and disturbance-sensitive systems, including Mecanum wheelchairs. Despite PSO's increased computing complexity during offline tuning and the necessity for meticulous parameter selection, its advantages can be precomputed and effectively utilized in real-time embedded systems. This study highlights the importance of safety, dependability, and responsiveness, illustrating that PSO is a scalable and efficient method for improving assistive robotic systems.

Author Biographies

Nuntachai Thongpance, Rangsit University

He currently holds the position of Associate Professor and Dean of the College of Biomedical Engineering at Rangsit University. He established undergraduate and graduate courses in medical instrumentation and biomedical engineering at Rangsit University. Nuntachai earned his Master of Engineering in nuclear technology from Chulalongkorn University in 1987 and his Bachelor of Science in physics with second-class honors from Prince of Songkla University in 1984. His research interests encompass medical devices, biomedical engineering, and healthcare management engineering.

Anantasak Wongkamhang, Rangsit University

He serves as a Lecturer in the Biomedical Engineering Program at the College of Biomedical Engineering, Rangsit University. He holds a Bachelor's degree in Medical Instrumentation from Rangsit University (2006) and a Master's degree in Biomedical Engineering from King Mongkut's Institute of Technology Ladkrabang (2014). His research interests span medical devices, equipment calibration, hospital engineering, microcontrollers, and instrumentation.

Rawiphon Chotikunnan, Rangsit University

He is a Lecturer in the Biomedical Engineering Program at the College of Biomedical Engineering, Rangsit University. With a Master of Engineering in Biomedical Engineering from Rangsit University and a Bachelor of Information Technology in Interactive Design and Game Development from Dhurakij Pundit University, his Research Interests Include Interactive Media, Medical Image Processing, Robots, and Control Systems.

Pariwat Imura, Rangsit University

He serves as a Lecturer in the Biomedical Engineering Program at the College of Biomedical Engineering, Rangsit University. He holds a Master of Engineering in Biomedical Engineering from Rangsit University and completed his Bachelor of Science Program in Computer Science at Rajamangala University of Technology Lanna. His research interests span Medical Imaging Systems, Fundamental Principles of Computer Communication Networks and Database Management, Smart Medical Systems, Big Data Analytics in Medical, Medical Artificial Intelligence, and embedded systems.

Wanida Khotakham, Rangsit University

She obtained her Bachelor of Engineering in Automation Engineering from King Mongkut's University of Technology Thonburi, Thailand and her Master of Science in Data Science from Newcastle University, UK. Currently, she is a lecturer in the College of Biomedical Engineering at Rangsit University, where she teaches courses on software design, health information technology, data analytics, and automation engineering.

Anuchit Nirapai, Rangsit University

He obtained his Bachelor of Science in Communication Engineering from Srinakharinwirot University, his Master of Science in Communication Engineering from King Mongkut's University of Technology North Bangkok, and his Doctor of Philosophy program in Information Technology Management from Mahidol University Thailand in 2008, 2015, and 2023, respectively. Presently, he holds a position as a lecturer in the College of Biomedical Engineering at Rangsit University. In this role, he instructs courses on software design, health information technology, information technology management, and the Internet of Medical Things (IoMT).

Kittipan Roongprasert, Rangsit University

He is a Lecturer in the Biomedical Engineering Program at the College of Biomedical Engineering, Rangsit University, with a Bachelor’s degree in Medical Instrumentation from Rangsit University (2006) and a Master’s degree in Biomedical Engineering from King Mongkut's Institute of Technology Ladkrabang (2016). His research interests include medical devices, equipment calibration, microcontrollers, and instrumentation.

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2025-04-28

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[1]
N. Thongpance, “Comparative Analysis of PID Tuning Methods for Speed Control in Mecanum-Wheel Electric Wheelchairs”, Buletin Ilmiah Sarjana Teknik Elektro, vol. 7, no. 2, pp. 95–110, Apr. 2025.

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Vol. 7 No. 2 (2025): June

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Copyright (c) 2025 Nuntachai Thongpance, Phichitphon Chotikunnan, Anantasak Wongkamhang, Rawiphon Chotikunnan, Pariwat Imura, Wanida Khotakham, Anuchit Nirapai, Kittipan Roongprasert

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