Migration & competition-based particle swarm optimization for parameter estimation
Ziwu Ren, Zhenhua Wang, Lining Sun · 2012
Enlightened by some knowledge of ecology and swarm competition, an improved multigrouped particle swarm optimization based on migration and competition, namely PSOMC, is proposed for parameters estimation of non-linear systems. The PSOMC is not concerned with the evolution of a single population, but instead is concerned with the evolution of multiple parallel swarms; moreover it incorporates some concepts, such as reintroduction, swarm competition, adjustment of swarm size, migration of particles between the swarm, and recycling, to enhance the global exploration ability and the local exploitation capability. Numerical simulations of two benchmark functions are used to test the performance of PSOMC. Furthermore, simulation on three different kinds of models is given to illustrate the effectiveness and efficiency of the proposed parameters estimation scheme.