摘要
针对火电厂主汽温被控对象的不确定性及大延迟、大惯性及非线性等特点,设计一种基于免疫遗传算法、BP神经网络和RBF神经网络的智能PID控制系统。利用免疫遗传算法的全局搜索寻优能力和较好的收敛性优化神经网络的权值,同时利用BP网络对PID参数进行在线调整。仿真结果表明,该系统在控制品质、鲁棒性方面都明显优于常规PID控制系统。
Considering the uncertainties,large delay and inertia and the nonlinear property of the main steam temperature control in power plant,a neural network intelligent PID control system based on immune genetic algorithm,BP neural network and RBF was designed;and basing on the global optimum capability and good convergence of the immune genetic algorithm,the weights of the neural network were optimized,and the PID parameters were adjusted by using BP network.The simulation results show that this system outperforms conventional PID control systems in control quality and robustness.
出处
《化工自动化及仪表》
CAS
北大核心
2011年第3期274-278,共5页
Control and Instruments in Chemical Industry
关键词
免疫遗传算法
神经网络
PID
主汽温
immune genetic algorithm
neural network
PID
main steam temperature
