Compressor Anti-Surge Nonlinear Model Predictive Control Based on LS-SVM

被引：0
|
作者：
Wang Chuan-Xin [1 ]
Shao Cheng [1 ]
Han Yu [2 ]
机构：
[1] Dalian Univ Technol, Inst Adv Control Technol, Dalian 116024, Peoples R China
[2] Dalian Univ Technol, Sch Software, Dalian 116620, Peoples R China
来源：
IMCIC 2010: INTERNATIONAL MULTI-CONFERENCE ON COMPLEXITY, INFORMATICS AND CYBERNETICS, VOL II | 2010年
关键词：
Anti-Surge Control; Predictive Control; LS-SVM; Genetic Algorithm; Compressor;
D O I：
暂无
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
An anti-surge nonlinear model predictive control system based on Least-Squared Support Vector Machine (LS-SVM) is proposed to increase the efficiency of compressor. In controller design, a compressor dynamic model is created by LS-SVM. A rolling optimization method combing genetic algorithm and LS-SVM is taken to get better real-time performance. Use the control signal of next equipment's inlet valve as feedforward to adjust the reference trajectory. Simulation and experiment are performed to show the effective of this method.
引用
收藏
页码：314 / 317
页数：4
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