An improved quantum particle swarm optimization and its application in system identification

In order to improve convergence speed and precision of optimization in quantum particle swarm optimization (QPSO), an improved quantum particle swarm optimization (IQPSO) algorithm was presented. Chaotic sequences were used to initialize the origin angle position of particle, mutation operation algorithm was used to increase diversity of population and avoid premature convergence. The proposed algorithm was applied to identify the classic adaptive infinite impulse response (IIR) model, the results show the validity of IQPSO.