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Collaborative position control of pantograph robot using particle swarm optimization

Ali, Nihad; Ayaz, Yasar; Iqbal, Jamshed


Nihad Ali

Yasar Ayaz


This article presents the design and real-time implementation of an optimal collaborative approach to obtain the desired trajectory tracking of two Degree of Freedom (DOF) pantograph end effector position. The proposed controller constructively synergizes the Proportional Integral Derivative (PID) and Linear Quadratic Regulator (LQR) by taking their weighted sum. Particle Swarm Optimization (PSO) algorithm is proposed to optimally tune the gains of PID, weighting matrices of LQR, and their ratio of contributions. Initially, the PID and LQR controller parameters are optimally tuned using PSO. In order to enhance the control effort and to provide more optimal performance, the weightages of each controller are optimally tuned and are kept constant. The collaborative position control strategy is tested against the PID and the LQR controllers via hardware in loop trials on a robotic manipulator. Experimental results are provided to validate the accurate trajectory tracking of the proposed controller. Results demonstrate that the optimal combination renders a significant improvement of 10% in steady state response and about 37% in transient response over the PID and LQR schemes.


Ali, N., Ayaz, Y., & Iqbal, J. (2022). Collaborative position control of pantograph robot using particle swarm optimization. International journal of control, automation, and systems, 20(1), 198-207.

Journal Article Type Article
Acceptance Date Mar 24, 2021
Online Publication Date Jan 17, 2022
Publication Date 2022
Deposit Date Sep 15, 2021
Publicly Available Date Jan 18, 2023
Journal International Journal of Control, Automation and Systems
Print ISSN 1598-6446
Electronic ISSN 2005-4092
Publisher Springer Verlag
Peer Reviewed Peer Reviewed
Volume 20
Issue 1
Pages 198-207
Keywords Optimal control; Pantograph; Particle swarm optimization; Robotics; Rotary servo; Tracking
Public URL


IJCAS Paper (7.3 Mb)

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