Fractional-Order Particle Swarm Optimization Alogrithm For Controller Tuning

In the era of big data,the development of swarm intelligence algorithm is accompanied by the progress of artificial intelligence,and the improvement of its algorithm and its application in the field of industrial control have gradually become a research hotspot.However,with rapid development of big data,data change is fast and is difficult to manage,lead to the traditional swarm intelligence model gradually fails to meet the requirements of complex problems in the real environment of big data.Therefore,the new swarm intelligence optimization algorithm designed to solve complex optimization problems in the big data environment is of great significance.At the same time,as an important part of industrial control field,PID controller has been widely concerned by many scholars at home and abroad.However,the traditional PID controller can not solve the complex problems in the current industrial control process.With the wide application of the new group intelligent optimization algorithm,it has successfully solved many complex problems in the field of industrial control,and the process of solving complex problems can be regarded as a parameter optimization problem.and the optimization objective of complex problem is to to solve the complex problems in the control field by combining swarm intelligence algorithm.Therefore,different optimization methods can be used to optimize PID controller parameters and improve the quality of system control.According to the above research background,the representative particle swarm optimization algorithm in swarm intelligence algorithm is selected and the basic PID controller in industrial control process as the theoretical basis of this paper,and conducts a series of research around the particle swarm optimization algorithm and PID controller,so the specific research content of this paper is as follows:1)The current research status of particle swarm optimization was analysed,and based on the theory of calculus,the fractional order particle swarm optimization algorithm is introduced,and according to the improvement scheme aiming at the advantages and disadvantages of relevant algorithms,a fractional order particle swarm optimization algorithm based on time factor was designed.According to the population diversity index and population evolution index,the degree of aggregation and dispersion of particles can be judged,adjusts the trajectory of particles in time,and updates the position and state information of particles,so as to improve the convergence performance of the algorithm.Then,a fractional particle swarm optimization algorithm based on dynamic compression factor is proposed to improve the global search ability.2)Around the problem that the parameter optimization of the traditional PID controller is not ideal in the process of system control,in view of the fractional order particle swarm optimization algorithm with time factor proposed in this paper,and combined with the research and analysis of PID controller,it is proved that the algorithm has good robustness in PID controller parameter optimization and eliminates the system error and the system output curve rise faster and stable.