A major difficulty in multivariable control design is the cross-coupling between inputs and outputs which obscures the effects of a specific controller on the overall behavior of the system. This paper considers the a...A major difficulty in multivariable control design is the cross-coupling between inputs and outputs which obscures the effects of a specific controller on the overall behavior of the system. This paper considers the application of kernel method in decoupling multivariable output feedback controllers. Simulation results are presented to show the feasibility of the proposed technique.展开更多
针对核电多回路耦合系统在升功率运行中异常传感器检测困难、检测延时及检测精度低等问题,提出了一种自联想核回归模型(auto-associative kernel regression,简称AAKR)与修正序贯概率比检验(sequential probability ratio test,简称SPRT...针对核电多回路耦合系统在升功率运行中异常传感器检测困难、检测延时及检测精度低等问题,提出了一种自联想核回归模型(auto-associative kernel regression,简称AAKR)与修正序贯概率比检验(sequential probability ratio test,简称SPRT)相结合的方法。首先,利用小波软阈值降噪方法对监测数据预处理,获取高质量的多源传感器解调信号;其次,采用AAKR构造传感器正常运行数据的估计值,并获取多源传感器测量值与估计值之间的残差;然后,运用滑动时间窗获取不同阶段残差向量的均值和方差,设计一种SPRT检测规则对传感器残差进行异常检测;最后,用核电一、二回路耦合系统模拟机实验数据进行方法验证与性能分析。结果表明,所提传感器异常检测方法的准确率达到99.52%,异常检测延时降低了81.73%,可有效提高现有核电厂传感器异常检测的稳定性。展开更多
工业控制系统面临的威胁增多,为做到主动防御,以及更加准确地识别入侵数据类型,基于工控蜜罐的部署环境,设计一种模型,用来识别入侵数据具体类型。首先对捕获的数据进行核主成分分析(Kernel Principal Component Analysis,KPCA)降维,然...工业控制系统面临的威胁增多,为做到主动防御,以及更加准确地识别入侵数据类型,基于工控蜜罐的部署环境,设计一种模型,用来识别入侵数据具体类型。首先对捕获的数据进行核主成分分析(Kernel Principal Component Analysis,KPCA)降维,然后利用Fisher算法对处理后的数据进行分类,如果判定为异常类,则再利用BP神经网络(Back Propagation neural network)进行二次判别,确定具体的入侵类别。实验结果表明,该方法检测率可达到95%,可以较好地对数据进行分类,判定具体的入侵类型。展开更多
文摘A major difficulty in multivariable control design is the cross-coupling between inputs and outputs which obscures the effects of a specific controller on the overall behavior of the system. This paper considers the application of kernel method in decoupling multivariable output feedback controllers. Simulation results are presented to show the feasibility of the proposed technique.
文摘针对核电多回路耦合系统在升功率运行中异常传感器检测困难、检测延时及检测精度低等问题,提出了一种自联想核回归模型(auto-associative kernel regression,简称AAKR)与修正序贯概率比检验(sequential probability ratio test,简称SPRT)相结合的方法。首先,利用小波软阈值降噪方法对监测数据预处理,获取高质量的多源传感器解调信号;其次,采用AAKR构造传感器正常运行数据的估计值,并获取多源传感器测量值与估计值之间的残差;然后,运用滑动时间窗获取不同阶段残差向量的均值和方差,设计一种SPRT检测规则对传感器残差进行异常检测;最后,用核电一、二回路耦合系统模拟机实验数据进行方法验证与性能分析。结果表明,所提传感器异常检测方法的准确率达到99.52%,异常检测延时降低了81.73%,可有效提高现有核电厂传感器异常检测的稳定性。
