Pole placement tuning of proportional integral derivative feedback controller for knee extension model

• Published in: Indonesian Journal of Electrical Engineering and Computer Science
• Main Author: Arof S.; Noorsal E.; Yahaya S.Z.; Hussain Z.; Radzali R.; Razak F.A.; Mustapha H.F.
• Format: Article
• Language: English
• Published: Institute of Advanced Engineering and Science 2024
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85190960335&doi=10.11591%2fijeecs.v34.i3.pp1566-1581&partnerID=40&md5=33f0a2570cc5e9bedd3b2113f1d7c9cd

Functional electrical stimulation (FES) has shown potential in rehabilitative exercises for patients recovering from spinal cord injuries. In recent developments, conventional open-loop FES control techniques have evolved into closed-loop systems that employ feedback controllers for automation. However, closed-loop FES systems often face challenges due to muscle non-linear effects, such as fatigue, time delays, stiffness, and spasticity. Therefore, an accurate non-linear knee model is required during the design stage, and precise tuning of the feedback controller parameters is vital. A proportional-integral-derivative (PID) controller is commonly used as a feedback controller due to its simplicity and ease of implementation. However, most PID tuning methods are complex and time consuming. This paper investigates the viability of employing the pole placement technique for tuning a PID controller that regulates the non-linear knee extension model. The pole placement method aims to improve the control and adaptability of the PID controller in closed-loop FES systems, specifically by facilitating knee extension exercises. MATLAB Simulink was used to assess the effectiveness of this tuning approach. Results showed that the PID controller performed satisfactorily without non-linearities, but performance varied with the inclusion of specific non-linearities. The pole placement tuning method facilitated preliminary assessments of PID controller performance, preceding highly advanced optimization. © 2024 Institute of Advanced Engineering and Science. All rights reserved.