Design and Low-Cost Implementation of an Electric Wheelchair Control

Abstract

This paper discusses the design and low-cost implementation of direction and speed controller for an electric wheelchair actuated using a permanent magnet direct current (PMDC) motor. Most of the works are performed either with the simulation of PMDC motor control with various techniques or studied the performance of a single type of controller in real-time with the wheelchair. In this work, the authors simulated the control of PMDC motor with three different controllers and tuned the parameters for real-time implementation of electric wheelchair control using PMDC motor. The authors attempted the simple solution using push button-based interface as well as a graphical user interface for the direction and speed control of electric wheelchair. The signal processing path of the controller, decode the user command input for the direction and desired speed. The controller generates necessary pulse width modulated signals to the H-bridge driver for directions forward, backward, left, and right direction as well as speed control of wheelchair. The user speed control commands low, slightly medium, medium, high, and very high speed are sensed to limit the speed of wheelchair. The performance capability of the intelligent neural network and fuzzy logic controller is studied and compared with proportional-integral-derivative (PID) controller with variations in speed. The PID, neural network and fuzzy logic controller are designed using Matlab-Simulink for PMDC motor and controller parameters are tuned for driving the wheelchair in the real-time implementation using the ATmega 328P microcontroller. The fuzzy logic controller in the electric wheelchair demonstrated the improved performance with less peak overshoot and faster settling with less oscillation compared to PID and neural network controller.

KEYWORDS:

• Arduino
• PMDC motor
• PI
• Rehabilitation
• Fuzzy logic
• Neural network
• Wheelchair

Acknowledgment

Thanks to the VIT University, Vellore for the support. Authors, also thank the reviewers for their valuable suggestions to improve the paper.

Additional information

Funding

Thanks to the Science and Engineering Research Board (SERB), Government of India, who has funded research project (No. SB/FTP/ETA-54/2013).

Notes on contributors

V. Sankardoss

V Sankardoss received his BE degree in electrical and electronics engineering from KS Rangasamy College of Technology, University of Madras, Tamil Nadu, India in 1999. He obtained MTech in electrical drives and control from Pondicherry Engineering College, Pondicherry University, Puducherry, India in 2005. Since 2007, he is with the School of Electrical Engineering, VIT University, Vellore, and also pursuing the PhD degree from VIT University, Vellore, Tamil Nadu. His research interest is electrical machines, electric wheelchair, control systems design, optimization techniques, solar energy and wind energy.Email: [email protected]

P. Geethanjali

P Geethanjali received her BE degree in electrical and electronics engineering from University of Madras, Tamilnadu, India in 2001. She obtained MTech in electrical drives and control from Pondicherry Engineering College, Puducherry, India in 2004. She received her PhD degree from VIT University, Vellore, India in 2012. Her PhD thesis has been nominated for “Best Thesis” by Indian National Academy of Engineering (INAE). She received grants from the Department of Science and Technology (DST), Government of India. She also received Fulbright-Nehru Academic and Professional Excellence Fellowship for 2014-15. Her research interests include bio-signal and image processing, pattern recognition, development of assistive devices, biomechanics and application of renewable energy in assistive devices.