Simulation of PID Control for DC Electronic Load Based on PSO Improved BP Algorithm
In order to address the problems of low sensitivity and stability in electronic load control,this paper put forward a method of controlling DC electronic load based on PSO-BP-PID.Firstly,the basic structure of the elec-tronic load was analyzed,and a mathematical model was constructed.Secondly,the current change rules of the elec-tronic load under different working modes were analyzed.Then,a three-layer BP network model was constructed,and the input and output content at each layer were described respectively.In order to improve the learning ability of the BP network and reduce control error,the PSO algorithm was used as a learning algorithm,and then particle swarm size,inertia weight,and other important parameters were determined.Finally,all particle fitness values were obtained.Next,the individual position and speed were continuously updated.When the convergence condition was met,the opti-mal solution was outputted.Finally,the control parameters were adjusted adaptively.According to the characteristics of the algorithm,the overall structure of the controller was designed.This controller could control the DC electronic loads.Simulation results show that the control error of the proposed method is small,and the response speed is fast.Meanwhile,harmonic waves can be effectively suppressed during the control process.
Particle swarm optimizationNeural networkPID controllerDC electronic loadLoad control
NETL
NSTL
万方数据
维普
