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    • 4. 发明授权
    • Automated tuning of large-scale multivariable model predictive controllers for spatially-distributed processes
    • 用于空间分布式过程的大规模多变量模型预测控制器的自动调整
    • US07650195B2
    • 2010-01-19
    • US11260809
    • 2005-10-27
    • Junqiang FanGregory E. Stewart
    • Junqiang FanGregory E. Stewart
    • G05B13/02
    • D21G9/0045G05B13/042
    • An automated tuning method of a large-scale multivariable model predictive controller for multiple array papermaking machine cross-directional (CD) processes can significantly improve the performance of the controller over traditional controllers. Paper machine CD processes are large-scale spatially-distributed dynamical systems. Due to these systems' (almost) spatially invariant nature, the closed-loop transfer functions are approximated by transfer matrices with rectangular circulant matrix blocks, whose input and output singular vectors are the Fourier components of dimension equivalent to either number of actuators or number of measurements. This approximation enables the model predictive controller for these systems to be tuned by a numerical search over optimization weights in order to shape the closed-loop transfer functions in the two-dimensional frequency domain for performance and robustness. A novel scaling method is used for scaling the inputs and outputs of the multivariable system in the spatial frequency domain.
    • 用于多阵列造纸机横向(CD)过程的大规模多变量模型预测控制器的自动调整方法可以显着提高控制器与传统控制器的性能。 造纸机CD过程是大规模的空间分布式动力系统。 由于这些系统(几乎)空间不变性质,闭环传递函数由具有矩形循环矩阵块的传递矩阵近似,其输入和输出奇异矢量是等效于执行器的数量或数量的傅立叶分量 测量。 这种近似使得能够通过优化权重的数值搜索来调整这些系统的模型预测控制器,以便在二维频域中形成闭环传递函数以获​​得性能和鲁棒性。 一种新的缩放方法用于缩放空间频域中多变量系统的输入和输出。
    • 5. 发明授权
    • Automatic tuning method for multivariable model predictive controllers
    • 多变量模型预测控制器的自动调谐方法
    • US07577483B2
    • 2009-08-18
    • US11442572
    • 2006-05-25
    • Junqiang FanGregory E. Stewart
    • Junqiang FanGregory E. Stewart
    • G06F19/00
    • G05B13/048G05B11/32
    • A fast and reliable technique for tuning multivariable model predictive controllers (MPCs) that accounts for performance and robustness is provided. Specifically, the technique automatically yields tuning weights for the MPC based on performance and robustness requirements. The tuning weights are parameters of closed-loop transfer functions which are directly linked to performance and robustness requirements. Automatically searching the tuning parameters in their proper ranges assures that the controller is optimal and robust. This technique will deliver the traditional requirements of stability, performance and robustness, while at the same time enabling users to design their closed-loop behavior in terms of the physical domain. The method permits the user to favor one measurement over another, or to use one actuator more than another.
    • 提供了一种用于调整考虑性能和鲁棒性的多变量模型预测控制器(MPC)的快速可靠的技术。 具体来说,该技术基于性能和鲁棒性要求自动产生MPC的调谐权重。 调谐权重是与性能和鲁棒性要求直接相关的闭环传递函数的参数。 自动搜索调谐参数在适当的范围内,确保控制器是最佳和稳健的。 这种技术将提供稳定性,性能和鲁棒性的传统要求,同时使用户能够根据物理域设计闭环行为。 该方法允许用户倾向于一次测量超过另一个,或者使用一个致动器多于另一个。
    • 7. 发明授权
    • Fast performance prediction of multivariable model predictive controller for paper machine cross-directional processes
    • 用于纸机横向过程的多变量模型预测控制器的快速性能预测
    • US07454253B2
    • 2008-11-18
    • US11393474
    • 2006-03-30
    • Junqiang Fan
    • Junqiang Fan
    • G06F19/00
    • G05B13/048
    • A technique for fast performance prediction of multivariable model predictive controllers (MPC) for large-scale spatially-distributed dynamic systems is provided. When operating an MPC for a two-dimensional sheetmaking process, the controller's performance can be separated into spatial performance and dynamic performance. The steady-state spatial performance for different sheet property modes is first predicted, thereafter, the dynamic performance is predicted on the basis of the steady-state actuator profiles. During the steady-state spatial performance prediction, the original MPC's cost function is approximated to be a steady-state cost function. Then the steady-state measurement profiles and the actuator profiles are calculated through the steady-state cost function. The actuator profiles in time series can be efficiently solved by minimizing the difference between the actuator profiles and the steady-state actuator profiles in the face of constraints. Finally, the model can be employed to expeditiously compute the measurement profiles in times series.
    • 提供了一种用于大规模空间分布式动态系统的多变量模型预测控制器(MPC)的快速性能预测技术。 当操作MPC进行二维制版过程时,控制器的性能可以分为空间性能和动态性能。 首先预测不同板材性能模式的稳态空间性能,此后,基于稳态致动器轮廓预测动态性能。 在稳态空间性能预测中,原始MPC的成本函数近似为稳态成本函数。 然后通过稳态成本函数计算稳态测量曲线和执行器曲线。 通过将约束条件下的致动器轮廓和稳态致动器轮廓之间的差最小化,可以有效地解决时间序列中的致动器轮廓。 最后,该模型可以用于快速计算时间序列中的测量曲线。
    • 8. 发明申请
    • Fast performance prediction of multivariable model predictive controller for paper machine cross-directional processes
    • 用于纸机横向过程的多变量模型预测控制器的快速性能预测
    • US20070239310A1
    • 2007-10-11
    • US11393474
    • 2006-03-30
    • Junqiang Fan
    • Junqiang Fan
    • G06F7/66
    • G05B13/048
    • A technique for fast performance prediction of multivariable model predictive controllers (MPC) for large-scale spatially-distributed dynamic systems is provided. When operating an MPC for a two-dimensional sheetmaking process, the controller's performance can be separated into spatial performance and dynamic performance. The steady-state spatial performance for different sheet property modes is first predicted, thereafter, the dynamic performance is predicted on the basis of the steady-state actuator profiles. During the steady-state spatial performance prediction, the original MPC's cost function is approximated to be a steady-state cost function. Then the steady-state measurement profiles and the actuator profiles are calculated through the steady-state cost function. The actuator profiles in time series can be efficiently solved by minimizing the difference between the actuator profiles and the steady-state actuator profiles in the face of constraints. Finally, the model can be employed to expeditiously compute the measurement profiles in times series.
    • 提供了一种用于大规模空间分布式动态系统的多变量模型预测控制器(MPC)的快速性能预测技术。 当操作MPC进行二维制版过程时,控制器的性能可以分为空间性能和动态性能。 首先预测不同板材性能模式的稳态空间性能,此后,基于稳态致动器轮廓预测动态性能。 在稳态空间性能预测中,原始MPC的成本函数近似为稳态成本函数。 然后通过稳态成本函数计算稳态测量曲线和执行器曲线。 通过将约束条件下的致动器轮廓和稳态致动器轮廓之间的差最小化,可以有效地解决时间序列中的致动器轮廓。 最后,该模型可以用于快速计算时间序列中的测量曲线。