Teaching particle swarm optimization through an open-loop system identification project.

ABSTRACT The particle swarm optimization (PSO), one of the most successful natural inspired algorithms, is revisited in the context of a proposal for a new teaching experiment. The problem considered is the open-loop step identification procedure, which is studied as an optimization problem. The PSO canonical algorithm main issues addressed within the proposed open-loop step identification experience are: the swarm random initialization methodology, the population size variation, and the inertia weight selection. The teaching experience learning outcomes are stated, simulation results presented, and feedback results from students analyzed. © 2011 Wiley Periodicals, Inc. Comput Appl Eng Educ 22:227-237, 2014; View this article online at ; DOI [ABSTRACT FROM AUTHOR]