Browsing by Author "Irfanoglu,B."

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Citation - Scopus: 56
Applications of the Extended Fractional Euler-Lagrange Equations Model To Freely Oscillating Dynamical Systems
(Publishing House of the Romanian Academy, 2016) Agila,A.; Baleanu,D.; Eid,R.; Irfanoglu,B.; Department of Mechatronics Engineering; Mathematics; 02. School of Arts and Sciences; 01. Atılım University
The fractional calculus and the calculus of variations are utilized to model and control complex dynamical systems. Those systems are presented more accurately by means of fractional models. In this study, an extended version of the fractional Euler-Lagrange equations is introduced. In these equations the damping force term is extended to be proportional to the fractional derivative of the displacement with variable fractional order. The finite difference methods and the Coimbra fractional derivative are used to approximate the solution of the introduced fractional Euler-Lagrange equations model. The free oscillating single pendulum system is investigated. © 2016, Editura Academiei Romane. All rights reserved.
Citation - Scopus: 3
Reciprocal Altruism-Based Path Planning Optimization for Multi-Agents
(Institute of Electrical and Electronics Engineers Inc., 2022) Maeedi,A.; Khan,M.U.; Irfanoglu,B.; Mechatronics Engineering; Department of Mechatronics Engineering; 15. Graduate School of Natural and Applied Sciences; 06. School Of Engineering; 01. Atılım University
This paper investigates solutions for the fundamental yet challenging problem of path planning of autonomous multi-agents. The novelty of the proposed algorithm, reciprocal altruism-based particle swarm optimization (RAPSO), lies in the introduction of information sharing among the agents. The RAPSO utilizes kinship relatedness among the agents during the optimization process to reciprocate the significant data. The concept of reciprocation is introduced to ensure that all agents remain in close contact through information exchange. The amount of exchange depends upon their physical location in the search space and their associated health indicator. Agents are classified as donors, recipients, or un-active concerning their health indicator and their positions. The ability of RAPSO to keep all agents closer to local optima through reciprocal altruism is evaluated for path planning optimization problem. Simulation results show that the RAPSO is very competitive when compared with the canonical PSO. The results of the generalized simulation scenario also prove its potential in solving path planning problems in robotics. © 2022 IEEE.