Model reduction based on improved hybrid particle swarm optimization

An improved hybrid particle swarm optimization algorithm (IHPSO) is proposed to deal with the problem of premature convergence and slow search speed in particle swarm optimization algorithm (PSO). New algorithm makes use of the principle of collision avoidance in BOIDS birds model and combine with Powell algorithm. This new algorithm is used to solve the model reduction problem in SESO system. In order to reduce the dimension of optimization, the numerator parameters are calculated by the least squares for each of candidates of the denominators parameters. Simulations based on benchmarks show the feasibility and effectiveness of the proposed method.