个人信息Personal Information
讲师
性别:女
毕业院校:韩国亚洲大学
学位:硕士
所在单位:软件学院、国际信息与软件学院
电子邮箱:yhan@dlut.edu.cn
Compressor Anti-Surge Nonlinear Model Predictive Control Based on LS-SVM
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论文类型:会议论文
发表时间:2010-04-06
收录刊物:EI、CPCI-S、Scopus
卷号:2
页面范围:314-317
关键字:Anti-Surge Control; Predictive Control; LS-SVM; Genetic Algorithm; Compressor
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.