期刊文献+

苯胺加氢反应过程的多变量解耦广义预测控制

Multi-variable Decoupling GPC System Design of the Aniline Hydrogenation Reaction
下载PDF
导出
摘要 针对苯胺加氢间歇反应具有高度不确定性和交叉耦合性,传统PID控制器很难达到理想控制品质,本文采用阶梯控制策略设计多变量广义预测控制(GPC)解耦控制系统。首先针对系统的交叉耦合性,对目标函数解耦算法进行了简化设计以有效减少计算量;然后利用GPC策略构建一个双输入双输出解耦GPC系统;最后将多变量解耦GPC控制与传统PID变结构控制进行对比分析,模拟仿真效果验证了该控制系统的有效性和强鲁棒性。 Due to the high degree of uncertainty and cross coupling, the traditional PID controller is difficult to achieve the ideal control quality. The step control strategy is used to design multi-variable decoupling generalized predictive control (GPC) control system. Firstly, considering the cross coupling of the system, the decoupling algorithm of the target function is reduced to reduce the amount of computation effectively. And the GPC is used to construct a dual input dual output decoupling GPC system. In the end, the multi-variable decoupling GPC control and the traditional PID variable structure control are compared and analyzed. The simulation results verify the effectiveness and robustness of the control system.
出处 《华东理工大学学报(自然科学版)》 CAS CSCD 北大核心 2016年第3期399-403,共5页 Journal of East China University of Science and Technology
基金 国家自然科学基金(61203020 21276126) 江苏省自然科学基金(BK20141461)
关键词 苯胺加氢反应 多变量解耦 广义预测控制(GPC) 间歇过程 aniline hydrogenation multi-variable decoupling GPC batch process
  • 相关文献

参考文献12

  • 1SRINIVASAN B, BONVIN D, VISSER E, et al. Dynamic optimization of batch processes~ I. Role of measurements in handling uncertainty I- J 1. Computers and Chemical Engineering, 2003,27 (1) : 27-44.
  • 2CHANG J S, CHEN K. An integrated strategy for early detection of hazardous states in chemical reactors I-J 3. Chemical Engineering Journal,2004,98(3) ~199-211.
  • 3BENKOUIDER A M,KESSAS R, YAHIAOUI A, et al. A hybrid approach to faults detection and diagnosis in batch and semi-batch reactors by using EKF and neural network classifier [J 1. Journal of Loss Prevention in the Process Industries, 2012,25 (4) 7694-702.
  • 4QIN S J,BADGWELL T A. An overview of nonlinear model predictive control applications[J']. Progress in Systems and Control Theory, 2000,26 (3) : 369-392.
  • 5CAI Wenjian, NI Wei, HE Maojun, et al. Normalized decoupling A new approach for MIMO process control system design [ J ~. Industrial ~ Engineering Chemistry Research, 2008,47 (19) ~ 7347-6356.
  • 6SKOGESTAD S, POSTLETHWAITE I. Multi Variable Feedback Control: Analysis and Design [M']. UK: Wiley, Chichester, 2005.
  • 7JEVTOVIC B T, MATAUSEK M R. PID controller design of TITO system based on ideal decouplerI-J~. Process Control, 2010,20 (7) ,869-876.
  • 8GARRIDO J, VAZQUEZ F, MORILLA F. Entralized multivariable control by simplified decoupling E J~. Process Control,2012,22(6) : 1044-1062.
  • 9CHI Qinghua,FEI Zhengshun, ZHAO Zhao, et al. A model predictive control approach with relevant identification in dynamic PLS frameworkl-Jl. Control Engineering Practice, 2013,22(1) :181-193.
  • 10EMBIRUCU M, FONTES C. Multirate muhivariable generalized predictive control and its application to a slurry reactor for ethylene polymerizationFJ~. Chemical Engineering Science, 2006,61 (17) : 5754-5767.

二级参考文献9

共引文献17

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部