Title: Advance genetic algorithm-based PID controller for air levitation system

Authors: Dwarkoba P. Gaikwad; Bharat S. Patil; Laxman S. Patil

Addresses: AISSMS College of Engineering, Pune, 411001, India ' AISSMS Polytechnic, Pune, 411001, India ' PVPIT, Sangli, 416304, India

Abstract: In industrial control systems, PID controllers are being widely used owing to their simple working principles. Many control and instruments engineers and operators use PID controllers in daily life. PID controllers allows for many variations which can cope with a wide range of systems and conditions. For increasing performances of PID controller, fine tuning of its parameters are required. Many authors have used different optimisation algorithms to tune parameters of PID controllers. These optimisation algorithms offer less performance. In this paper, the fine-tuned PID controller have proposed for the air levitation system. Advanced genetic algorithm is used for tuning parameters of PID controllers. For demonstration of efficiency and applicability of the proposed PID controller, simulation-based experimentations have been conducted. The proposed PID design method has been linked with other three optimisation techniques. Ant colony optimisation, particle swarm optimisation and fuzzy logic have been used for performances comparison of advanced genetic algorithm-based PID controllers. In experimental results, we have got very smallest value of IAE, ISE and ITAE using proposed method. It indicates that the proposed PID design method offers better performances than other three optimisation-based PID design methods and other existing methods.

Keywords: PID; integrating; process model; tuning; stability.

DOI: 10.1504/IJMIC.2022.127519

International Journal of Modelling, Identification and Control, 2022 Vol.41 No.3, pp.243 - 255

Received: 17 Sep 2021
Accepted: 16 Dec 2021

Published online: 07 Dec 2022 *

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