This paper proposes a decoupling control scheme with two-degrees-of-freedom (2DOF) control structure. In the proposed scheme, two multivariable controllers are designed based on Internal Model Control (IMC) theory for...This paper proposes a decoupling control scheme with two-degrees-of-freedom (2DOF) control structure. In the proposed scheme, two multivariable controllers are designed based on Internal Model Control (IMC) theory for setpoint tracking and disturbance rejection independently. An analytical approximation method is utilized to reduce the order of the controllers. By adjusting the corresponding controller parameter, the setpoint tracking and disturbance rejection of each control loop can be tuned independently. In the presence of multiplicative input uncertainty, a calculation method is also proposed to derive the low bounds of the control parameters in order to guarantee the robust stability of the system. Simulations are illustrated to demonstrate the validity of the proposed control scheme.展开更多
多元控制图常用于对多个相关变量进行监控,用以发现制造过程中存在的系统性变异。当多元过程的分布未知时,常用非参数方法进行过程监控。针对多元过程监控问题,提出了一种基于最小二乘支持向量机(least squares support vector machine,...多元控制图常用于对多个相关变量进行监控,用以发现制造过程中存在的系统性变异。当多元过程的分布未知时,常用非参数方法进行过程监控。针对多元过程监控问题,提出了一种基于最小二乘支持向量机(least squares support vector machine,LSSVM)的多元过程非参数监控方法。在仅有受控数据(参考数据集)的条件下,采用移动窗口技术对过程数据序列进行预处理,并与参考数据集一起用于对LSSVM进行动态训练,进而以移动窗口中的数据与分类超平面之间的距离为控制变量进行多元过程监控。讨论了监控模型设计与参数选择方法并通过仿真和实例进行了性能评估。展开更多
基金NSFC (No.60704021,60474031) , NCET (No.04-0383)Australia-China Special Fund for Scientific & Technological Cooperation
文摘This paper proposes a decoupling control scheme with two-degrees-of-freedom (2DOF) control structure. In the proposed scheme, two multivariable controllers are designed based on Internal Model Control (IMC) theory for setpoint tracking and disturbance rejection independently. An analytical approximation method is utilized to reduce the order of the controllers. By adjusting the corresponding controller parameter, the setpoint tracking and disturbance rejection of each control loop can be tuned independently. In the presence of multiplicative input uncertainty, a calculation method is also proposed to derive the low bounds of the control parameters in order to guarantee the robust stability of the system. Simulations are illustrated to demonstrate the validity of the proposed control scheme.
文摘多元控制图常用于对多个相关变量进行监控,用以发现制造过程中存在的系统性变异。当多元过程的分布未知时,常用非参数方法进行过程监控。针对多元过程监控问题,提出了一种基于最小二乘支持向量机(least squares support vector machine,LSSVM)的多元过程非参数监控方法。在仅有受控数据(参考数据集)的条件下,采用移动窗口技术对过程数据序列进行预处理,并与参考数据集一起用于对LSSVM进行动态训练,进而以移动窗口中的数据与分类超平面之间的距离为控制变量进行多元过程监控。讨论了监控模型设计与参数选择方法并通过仿真和实例进行了性能评估。
