Citation

Goud, Harsh and Chandra Sharma, Prakash and Nisar, Kashif and Haque, Muhammad Reazul and Ag. Ibrahim, Ag. Asri and Singh Yadav, Narendra and Swarnkar, Pankaj and Gupta, Manoj and Chand, Laxmi (2022) Metaheuristics Algorithm for Tuning of PID Controller of Mobile Robot System. Computers, Materials & Continua, 72 (2). pp. 3481-3492. ISSN 1546-2226

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Abstract

Robots in the medical industry are becoming more common in daily life because of various advantages such as quick response, less human interference, high dependability, improved hygiene, and reduced aging effects. That is why, in recent years, robotic aid has emerged as a blossoming solution to many challenges in the medical industry. In this manuscript, meta-heuristics (MH) algorithms, specifically the Firefly Algorithm (FF) and Genetic Algorithm (GA), are applied to tune PID controller constraints such as Proportional gain Kp Integral gain Ki and Derivative gain Kd. The controller is used to control Mobile Robot System (MRS) at the required set point. The FF arrangements are made based on various pre-analysis. A detailed simulation study indicates that the proposed PID controller tuned with Firefly Algorithm (FF-PID) for MRS is beneficial and suitable to achieve desired closed-loop system response. The FF is touted as providing an easy, reliable, and efficient tuning technique for PID controllers. The most suitable ideal performance is accomplished with FF-PID, according to the display in the time response. Further, the observed response is compared to those received by applying GA and conventional off-line tuning techniques. The comparison of all tuning methods exhibits supremacy of FF-PID tuning of the given nonlinear Mobile Robot System than GA-PID tuning and conventional controller.

Item Type:	Article
Uncontrolled Keywords:	Metaheuristic algorithm, genetic algorithm, PID controller, mobile robot system, firefly algorithm
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines
Divisions:	Faculty of Computing and Informatics (FCI)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	03 Nov 2022 02:00
Last Modified:	03 Nov 2022 02:00
URII:	http://shdl.mmu.edu.my/id/eprint/10197

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