摘要
为提高称重配料过程的控制精度,探讨了基于径向基神经网络(RBFNN)辨识的模型预测控制(MPC)系统的应用,着重介绍了径向基神经网络的特点,模型预测控制特性,提出了以径向基神经网络作为预测器和控制器的模型预测控制系统。实践证明,该系统可以改进被控对象的性能,适用于较为复杂的不确定性强的非线性控制对象。目前已成功在福建某钢铁厂烧结料场控制系统改造项目中投入使用,并取得了良好的控制效果,该系统在钢铁冶炼烧结称重环节不同料种圆盘中有广阔的应用前景。
To improve control precision in weight control process,the application of predictive weight control system based on RBFNN is intro- duced.Characteristics of RBFNN and MPC and the use of RBFNN as predictor and controller in MPC are given.Practical results show that the system can improve the control performance and it's suitable for complicated and unconfirmed non-linear control objections.The system is suc- cessfully used in steel sinter control system improvement project of a Fujian steel plant,and obtaines nice control performance.It can he widely used in different hoppers of steel sinter weight process.
出处
《控制工程》
CSCD
2006年第S2期47-49,114,共4页
Control Engineering of China