摘要
针对化工过程中普遍存在的非线性和时变特性,提出了一种基于递推子空间辨识的自适应预测控制策略.用子空间辨识法得到的预测模型作为初始模型,通过比较初始模型和在线更新模型的匹配误差,选择匹配误差较小的预测模型计算过程的输入,从而提高了模型精度.通过模拟移动床过程控制的仿真试验,表明该方法具有较强的鲁棒性和抗干扰能力.
To deal with the nonlinearity and time-varying characteristics in the processes of chemical industry, an adaptive-predictive-control strategy based on the recursive subspace identification is proposed. The predictive models obtained from the subspace identification are considered the initial models, which are compared with the online updated model to generate matching errors. The model with the smallest matching error is selected for use in calculating the process control input, thus improving the model accuracy. The control simulations of a simulated moving bed（SMB） show that the method is robust to the system parameters perturbation and efficient in attenuating external disturbance.
出处
《控制理论与应用》
EI
CAS
CSCD
北大核心
2009年第3期313-315,共3页
Control Theory & Applications
基金
国家高技术研究发展计划(2007AA041403).
关键词
子空间辨识
自适应控制
匹配误差
模拟移动床
subspace identification
adaptive control
matching error
simulated moving bed
