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All Journal Sinergi TEKNOKOM : Jurnal Teknologi dan Rekayasa Sistem Komputer
Tian, Yingzhong
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering

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AN FLC-PSO ALGORITHM-CONTROLLED MOBILE ROBOT Suwoyo, Heru; Tian, Yingzhong; Ibnu Hajar, Muhammad Hafizd
SINERGI Vol 24, No 3 (2020)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2020.3.002

Abstract

The ineffectiveness of the wall-following robot (WFR) performance indicated by its surging movement has been a concerning issue. The use of a Fuzzy Logic Controller (FLC) has been considered to be an option to mitigate this problem. However, the determination of the membership function of the input value precisely adds to this problem. For this reason, a particular manner is recommended to improve the performance of FLC. This paper describes an optimization method, Particle Swarm Optimization (PSO), used to automatically determinate and arrange the FLC’s input membership function. The proposed method is simulated and validated by using MATLAB. The results are compared in terms of accumulative error. According to all the comparative results, the stability and effectiveness of the proposed method have been significantly satisfied.
THE ACA-BASED PID CONTROLLER FOR ENHANCING A WHEELED-MOBILE ROBOT Suwoyo, Heru; Thong, Zhou; Tian, Yingzhong; Adriansyah, Andi; Ibnu Hajar, Muhammad Hafizd
TEKNOKOM Vol. 5 No. 1 (2022): TEKNOKOM
Publisher : Department of Computer Engineering, Universitas Wiralodra

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (734.663 KB) | DOI: 10.31943/teknokom.v5i1.74

Abstract

Wall-following control of mobile robot is an important topic in the mobile robot researches. The wall-following control problem is characterized by moving the robot along the wall in a desired direction while maintaining a constants distance to the wall. The existing control algorithms become complicated in implementation and not efficient enough. Ant colony algorithm (ACA), in terms of optimizing parameters, has a faster convergence speed and features that are easy to integrate with other methods. This paper adopts ant colony algorithm to optimize PID controller, and then selects ideal control parameters. The simulation results based on MATLAB show that the control system optimized by ant colony algorithm has higher efficiency than the traditional control systems in term of RMSE.
Co-Authors Andi Adriansyah Hossain, Md Musabbir Ibnu Hajar, Muhammad Hafizd Li, Long Suwoyo, Heru Thong, Zhou Wang, Wenbin