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Optimal PID Design Approaches for an Inverted Pendulum System

Muhammad Sani Gaya(1*), Anas Abubakar Bisu(2), Syed Najib Syed Salim(3), I. S. Madugu(4), L. A. Yusuf(5), M. L. Kaurangini(6), M. T. M. Khairi(7)

(1) Department of Electrical Engineering, Kano University of Science and Technology, Wudil, Nigeria
(2) Department of Physics, Bayero University Kano, Nigeria
(3) Dept. Industrial automation and Robotic, Universiti Teknikal Malaysia, Malaysia
(4) Department of Electrical Engineering, Kano University of Science and Technology, Wudil, Nigeria
(5) Department of Electrical Engineering, Bayero University Kano, Nigeria
(6) Dept. of Mathematics, Kano University of Science and Technology, Wudil, Nigeria
(7) Control and Mechatronics Engineering Dept., Universiti Teknologi Malaysia, Malaysia
(*) Corresponding author


DOI: https://doi.org/10.15866/ireaco.v9i3.9160

Abstract


Instability may cause a system to move dangerously and suffer bodily damage, which can become costly. One of the reasons for designing control systems is to stabilize an unstable system. However, control of unstable systems is primarily more difficult either due to lack of precise description of the system or incompletely modelled disturbances. Application of a classical control algorithm does not mostly yield the desired results. Advanced control is expensive and intelligent control has parameters' choice/tuning issues. This paper presents a comparison of optimal Proportional Integral Derivative (PID) controller design techniques for an inverted pendulum. The optimization approaches considered are the swarm intelligent based algorithm (Particle Swarm Optimization [PSO]) and Enhanced Nonlinear PID (EN-PID). The performances of the controllers were evaluated based on stabilizing the angle of the pendulum and disturbance rejection. Simulation results revealed that the PSO-PID outperformed the EN-PID and PID in maintaining the pendulum vertically and demonstrated an attractive ability in rejecting disturbances as compared to the PID and EN-PID. The PSO-PID may serve as a useful control algorithm for the system.
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Keywords


Pendulum; PID; Nonlinear; Optimization; Particle; Swarm; Gain

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