The Study Of PID Parameters Setting Based On Improved PSO Algorithm

PID control is a very classic process control in the industrial production, it is widely used in the industrial process control for its simple structure and easy setting in practical applications. The rapid development of Industrial production make the process control more complex, the PID parameter setting methods used in the past can no longer meet the higher requirements of modern process control, it is urgent to study a new and efficient method meet the rapid development of modern industrial production.Particle swarm optimization (PSO) is based on a group of intelligent optimization process of migrating birds foraging and gathering simulation algorithms. It cause great attention and widely used in the field of science and engineering for easy to understand, easy to implement and strong global search capability.PSO is introduced into the PID controller parameter setting in this paper, in order to realize the optimal parameter setting. The main work is as follows:(1) A mean PSO algorithm based on adaptive inertia weight optimization algorithm is proposed. Its improvement strategy as follows:1) Particle classification. The particle is divided into three levels through the fitness value’s comparison; 2) Adaptive inertia weight strategy. The particles using different inertia weight according to the classification results; 3) Linear combination of individual extreme and global extremes. The individual and global optima are replaced by their linear combination during the iteration of algorithm. The tests proved that the optimization algorithm has better performance and is a more effective and fast particle swarm optimization.(2) The improved particle swarm optimization algorithm is applied to PID parameter setting. Through four typical controlled object simulation and comparative show that the MPAPSO-PID setting algorithm is an effective parameter optimization algorithm, which can improve the performance of the control system. Finally, an example of the industrial furnace temperature control simulation model is established, to further demonstrate the effectiveness and efficiency of the improved PID setting parameters of particle swarm algorithm.Finally, we summarized what the work this article has done proposed the further research content.