Predictability of Impact Force Localization by Using the Optimization Technique. (2016)

• Record Type: Journal Article
• Authors: El-Bakari, Abdelali; Teidj, Sara; Khamlichi, Abdellatif; Jacquelin, Eric
• Is Part Of: Procedia technology. Volume 22(2016)
• Page Start: 94
• Page End: 100
• Publication Date: 2016
• Subjects: Particle swarm optimization -- Genetic algorithm -- Localization -- Impact force -- Stability coefficients control -- Convergence.; Technology -- Congresses; Technology -- Periodicals; Engineering -- Congresses; Engineering -- Periodicals; Engineering; Technology; Conference proceedings; Periodicals; 605
• DOI: 10.1016/j.protcy.2016.01.015
• Languages: English
• ISSNs: 2212-0173

Abstract

Abstract: This work focuses on the analysis of some parameters that govern convergence of an adapted version of Particle Swarm Optimization and genetic algorithm which are used for identifying location of an impact occurring on an elastic beam structure. The problem takes the form of population number, the acceleration coefficients and a constrained nonlinear mathematical program for which the fitness function is obtained through Maxwell-Betti theorem. Sensors are assumed to be implemented in judiciously chosen locations and emphasis is done on the geometrical constraints that are introduce to limit the possible domain of impact location as well as on the stability coefficients that are specified in PSO and GA algorithms. It was found both that the chosen constraints, population number and stability coefficients control to large extent performance of these algorithms.