A Comparison of Differential Evolution, Particle Swarm Optimization and Genetic Algorithms for the Identification of Bouc-Wen Hysteretic Systems
نویسنده
چکیده
In this paper, several variants of Differential Evolution, Particle Swarm Optimization and Genetic Algorithms are employed for the identification of a BoucWen hysteretic system that represents a full-scale bolted-welded steel connection. The purpose of this work is to assess their comparative performance in a highly nonlinear identification problem. Interesting results are produced that reveal the strengths and weaknesses of each algorithm.
منابع مشابه
Non-linear Fractional-Order Chaotic Systems Identification with Approximated Fractional-Order Derivative based on a Hybrid Particle Swarm Optimization-Genetic Algorithm Method
Although many mathematicians have searched on the fractional calculus since many years ago, but its application in engineering, especially in modeling and control, does not have many antecedents. Since there are much freedom in choosing the order of differentiator and integrator in fractional calculus, it is possible to model the physical systems accurately. This paper deals with time-domain id...
متن کاملEfficient Data Mining with Evolutionary Algorithms for Cloud Computing Application
With the rapid development of the internet, the amount of information and data which are produced, are extremely massive. Hence, client will be confused with huge amount of data, and it is difficult to understand which ones are useful. Data mining can overcome this problem. While data mining is using on cloud computing, it is reducing time of processing, energy usage and costs. As the speed of ...
متن کاملEffects of Mathematical Model of MR Damper on Its Control Performance; A Nonlinear Comparative Study
In this paper, the effect of mathematical representation method of an MR damper on the performance of control algorithm is investigated. The most exact and common Maxwel Nonlinear Slider (MNS) and modified Bouc-Wen hysteretic models are employed through a nonlinear comparatve numerical study. In many of semi-active control algorithms, a mathematical modelling method is required for determinig ...
متن کاملParameter identification of Magnetorheological damper using particle swarm optimization
Particle swarm optimization (PSO) technique has achieved a considerable success in solving nonlinear, nondifferentiable, multi-modal optimization problems. Currently, PSO is broadly applied in several scientific and engineering optimization applications. This paper introduces an identification of magnetorheological (MR) damper’s parameters using the PSO algorithm to introduce a more simple and ...
متن کاملA Comparative Study of Four Evolutionary Algorithms for Economic and Economic-Statistical Designs of MEWMA Control Charts
The multivariate exponentially weighted moving average (MEWMA) control chart is one of the best statistical control chart that are usually used to detect simultaneous small deviations on the mean of more than one cross-correlated quality characteristics. The economic design of MEWMA control charts involves solving a combinatorial optimization model that is composed of a nonlinear cost function ...
متن کامل