Application Of Optimization Of HSIC Parameter Based On Particle Swarm Optimization

Human-simulated intelligent control shows it's unique advance in solving complex system, however One of main problems when applying human-simulated intelligent control is parameters optimization of controllers. With the increasing of complexity of systems, the structure of human-simulated intelligent controller becomes also more and more complex,therefore there is much difficulty for some experts in the parameters optimization. Hereby, the paper developed a method resolving the parameters optimization of human-simulated intelligent controller based on evolution thought.Particle Swarm Optimization (PSO) has been proposed to solve this parameters optimization problem. As a relatively new evolutionary computation, PSO algorithm applies the information communication within particles to update itself, instead of any genetic operator such as crossover and mutation. All the particles are able to adjust their velocity and remember the best position in the past. This optimization algorithm has been applied to many engineering problem successfully.PSO is an efficient stochastic global optimization technique, however PSO algorithm will stuck at local optima easily. Aiming at disadvantage of classical PSO algorithm, this paper put forward some new improved algorithm and proved that improved PSO is effective and feasible.In the research process, the following works have been completed:①Synthesis the history and the current research progress of Computational Intelligence and PSO research conditions.②Summarize the principles of PSO and put forward some improved PSO.③Research on HSIC and choose one of improved PSO to optimize HSIC parameter.Practices demonstrate the effectiveness of proposed methods resolving the parameters optimization problems of human-simulated intelligent controller based on evolution thought.