A modified fruit fly optimization algorithm and its application to control of robot manipulators

Mehdifar, Farhad; Gholami, Hassan; Kharrati, Hamed; Menhaj, Mohammad Bagher

doi:10.1109/icciautom.2017.8258664

Cited by 4 publications

(2 citation statements)

References 17 publications

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“…The implementation of a searching technique in robotics can benefit some aspects such as for military usage [1], and disaster mitigation in the hazardous area [2]. Then, the implementation with a similar technique has been implemented such as locating a food source [3] and locating a gas leakage source [4].…”

Section: Introductionmentioning

confidence: 99%

Gas Source Localization Using Bio-inspired Algorithm for Mini Flying Sniffer Robot: Development and Experimental Investigation

Fikri

2020

ComEngApp

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In this paper, we demonstrated a gas source localization (GSL) using a mini quadrotor as a mini flying sniffer robot. The algorithm employed is based on a bioinspired algorithm from insect behavioral searching and it is constrained to perform only in 2D dimension open space area. In this study, we deliver some information such as system development, and algorithm flowchart to highlight how this study can achieve the target goal. The performance of insect behavioral based for searching the source location shows an interesting result. Where we can achieve a satisfactory result to find the source position using a bioinspired algorithm. The experimental results are provided to evaluate the performance of the searching algorithm.

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Section: Introductionmentioning

confidence: 99%

Gas Source Localization Using Bio-inspired Algorithm for Mini Flying Sniffer Robot: Development and Experimental Investigation

Fikri

2020

ComEngApp

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“…In order to control two-degree-of-freedom (2-DOF) robot manipulator, Elkhateeb and Badr in [30] applied the bee colony algorithm to tune the PID controller. A modified version fruit fly optimization algorithm (MFOA) is also used to find the optimal PID parameters where nonlinear robot's dynamic is linearized and decoupled using a nonlinear feedback linearization control technique [31]. In the same context, a new modified biogeography-based optimization (BBO) algorithm is developed to tune PID parameters of a five bar robot [32].…”

Section: Introductionmentioning

confidence: 99%

Whale optimizer algorithm to tune PID controller for the trajectory tracking control of robot manipulator

Loucif

Kechida

Sebbagh

2019

J Braz. Soc. Mech. Sci. Eng.

173

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In this work, we are interested to the PID control of nonlinear systems and more specially the control of a robot manipulator. The idea is to determine the optimal parameters (K p , K i and K d) of the controller using a novel algorithm of optimization called whale optimizer algorithm (WOA). To study the effectiveness of WOA-PID controller, its performance is compared with other controllers such as particle swarm optimization-PID (PSO-PID) and grey wolf optimizer-PID (GWO-PID). The model of robot manipulator and all controllers were tested using Simulink/MATLAB. Simulation results obtained clearly indicate the superiority of WOA-PID controller over the other controllers for trajectory tracking, better settling time, and ITAE errors.

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A systematic review on fruit fly optimization algorithm and its applications

Ranjan

Kumar

2023

Artif Intell Rev

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A modified fruit fly optimization algorithm and its application to control of robot manipulators

Cited by 4 publications

References 17 publications

Gas Source Localization Using Bio-inspired Algorithm for Mini Flying Sniffer Robot: Development and Experimental Investigation

Gas Source Localization Using Bio-inspired Algorithm for Mini Flying Sniffer Robot: Development and Experimental Investigation

Whale optimizer algorithm to tune PID controller for the trajectory tracking control of robot manipulator

A systematic review on fruit fly optimization algorithm and its applications

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