关键词:

制粉系统, 解耦控制技术, PID神经网络, 粒子群优化算法

Abstract:

Ball mill coal pulverizing system of pelletizing plant is a complex nonlinear multivariable process with strongly coupling and time-delay，and its operation often varies significantly. The automatic control of such a system is a research focus in the process control area. A multivariable adaptive PID artificial neural network（ANN）controller was introduced，which was based on the characteristics of particle swarm optimization（PSO）algorithm searching the parameter space concurrently and efficiently，and the self-regulation and adaptability of PID artificial neuron networks. Decoupling control technology based on the PID-ANN was used to eliminate the coupling between loops. Particle swarm optimization algorithm was also adopted to optimize the weights of neural networks. Simulation results showed that controller method proposed had better control quality，adaptive decoupling ability and self-learning function. The new control strategy could overcome nonlinear and strong coupling features of the system in a wide range and is expected to have great potential for engineering application.

Key words:

制粉系统, 解耦控制技术, PID神经网络, 粒子群优化算法