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11. 发明授权

US07024252B2 Kiln thermal and combustion control 失效
标题翻译：窑炉和燃烧控制
公开(公告)号：US07024252B2
公开(公告)日：2006-04-04
申请号：US11234927
申请日：2005-09-26
申请人： Gregory D. Martin , Eugene Boe , Stephen Piche , James David Keeler , Douglas Timmer , Mark Gerules , John P. Havener
发明人： Gregory D. Martin , Eugene Boe , Stephen Piche , James David Keeler , Douglas Timmer , Mark Gerules , John P. Havener
IPC分类号： G05B13/02
CPC分类号： G05B13/048 , G05B13/042 , G05B17/02
摘要： A method and apparatus for controlling a non-linear mill. A linear controller is provided having a linear gain k that is operable to receive inputs representing measured variables of the plant and predict on an output of the linear controller predicted control values for manipulatible variables that control the plant. A non-linear model of the plant is provided for storing a representation of the plant over a trained region of the operating input space and having a steady-state gain K associated therewith. The gain k of the linear model is adjusted with the gain K of the non-linear model in accordance with a predetermined relationship as the measured variables change the operating region of the input space at which the linear controller is predicting the values for the manipulatible variables. The predicted manipulatible variables are then output after the step of adjusting the gain k.
摘要翻译：一种用于控制非线性磨机的方法和装置。提供具有线性增益k的线性控制器，其可操作以接收表示工厂的测量变量的输入，并且对线性控制器的输出预测用于控制工厂的操纵性变量的预测控制值。提供工厂的非线性模型，用于在工作输入空间的经过训练的区域上存储工厂的表示，并具有与其相关联的稳态增益K. 线性模型的增益k根据预定的关系用非线性模型的增益K进行调整，因为测量的变量改变了线性控制器预测操作变量的值的输入空间的操作区域。然后在调整增益k的步骤之后输出预测的操纵变量。

12. 发明授权

US06493596B1 Method and apparatus for controlling a non-linear mill 有权
标题翻译：用于控制非线性磨机的方法和装置
公开(公告)号：US06493596B1
公开(公告)日：2002-12-10
申请号：US09514733
申请日：2000-02-28
申请人： Gregory D. Martin , Eugene Boe , Stephen Piche , James David Keller , Douglas Timmer , Mark Gerules , John P. Havener
发明人： Gregory D. Martin , Eugene Boe , Stephen Piche , James David Keller , Douglas Timmer , Mark Gerules , John P. Havener
IPC分类号： G05B1302
CPC分类号： G05B13/048 , G05B13/042 , G05B17/02
摘要： A method and apparatus for controlling a non-linear mill. A linear controller is provided having a linear gain k that is operable to receive inputs representing measured variables of the plant and predict on an output of the linear controller predicted control values for manipulatible variables that control the plant. A non-linear model of the plant is provided for storing a representation of the plant over a trained region of the operating input space and having a steady-state gain K associated therewith. The gain k of the linear model is adjusted with the gain K of the non-linear model in accordance with a predetermined relationship as the measured variables change the operating region of the input space at which the linear controller is predicting the values for the manipulatible variables. The predicted manipulatible variables are then output after the step of adjusting the gain k.
摘要翻译：一种用于控制非线性磨机的方法和装置。提供具有线性增益k的线性控制器，其可操作以接收表示工厂的测量变量的输入，并且对线性控制器的输出预测用于控制工厂的操纵性变量的预测控制值。提供工厂的非线性模型，用于在工作输入空间的经过训练的区域上存储工厂的表示，并具有与其相关联的稳态增益K. 线性模型的增益k根据预定的关系用非线性模型的增益K进行调整，因为测量的变量改变了线性控制器预测操作变量的值的输入空间的操作区域。然后在调整增益k的步骤之后输出预测的操纵变量。

13. 发明申请

US20060100720A1 Kiln free lime control 有权
标题翻译：窑炉免费石灰控制
公开(公告)号：US20060100720A1
公开(公告)日：2006-05-11
申请号：US11317499
申请日：2005-12-22
申请人： Gregory Martin , Eugene Boe , Stephen Piche , James Keeler , Douglas Timmer , Mark Gerules , John Havener , Steven McGarel
发明人： Gregory Martin , Eugene Boe , Stephen Piche , James Keeler , Douglas Timmer , Mark Gerules , John Havener , Steven McGarel
IPC分类号： G05B13/02
CPC分类号： G05B13/048 , G05B13/042 , G05B17/02
摘要： A kiln thermal and combustion control. A predictive model is provided of the dynamics of selected aspects of the operation of the system for modeling the dynamics thereof. The model has at least two discrete models associated therewith that model at least two of the selected aspects, the at least two discrete models having different dynamic responses. An optimizer receives desired values for the selected aspects of the operation of the system modeled by the model and optimizes the inputs to the model to minimize error between the predicted and desired values. A control input device then applies the optimized input values to the system after optimization thereof.
摘要翻译：窑炉和燃烧控制。提供了用于对其动力学进行建模的系统的操作的选定方面的动态的预测模型。所述模型具有至少两个与之相关的离散模型，所述至少两个所选择的方面模型，所述至少两个离散模型具有不同的动态响应。优化器接收由模型建模的系统的操作的所选方面的期望值，并优化对模型的输入以最小化预测值和期望值之间的误差。然后，控制输入装置优化后对系统施加优化的输入值。

14. 发明申请

US20050075737A1 Method and apparatus for modeling dynamic and steady-state processes for prediction, control and optimization 有权
标题翻译：用于预测，控制和优化的动态和稳态过程建模的方法和装置
公开(公告)号：US20050075737A1
公开(公告)日：2005-04-07
申请号：US10847211
申请日：2004-05-17
申请人： Gregory Martin , Eugene Boe , Stephen Piche , James Keeler , Douglas Timmer , Mark Gerules , John Havener
发明人： Gregory Martin , Eugene Boe , Stephen Piche , James Keeler , Douglas Timmer , Mark Gerules , John Havener
IPC分类号： G05B13/02 , G05B13/04 , G05B17/02 , G05B21/02
CPC分类号： G05B17/02 , G05B13/048
摘要： A method for providing independent static and dynamic models in a prediction, control and optimization environment utilizes an independent static model (20) and an independent dynamic model (22). The static model (20) is a rigorous predictive model that is trained over a wide range of data, whereas the dynamic model (22) is trained over a narrow range of data. The gain K of the static model (20) is utilized to scale the gain k of the dynamic model (22). The forced dynamic portion of the model (22) referred to as the bi variables are scaled by the ratio of the gains K and k. The bi have a direct effect on the gain of a dynamic model (22). This is facilitated by a coefficient modification block (40). Thereafter, the difference between the new value input to the static model (20) and the prior steady-state value is utilized as an input to the dynamic model (22). The predicted dynamic output is then summed with the previous steady-state value to provide a predicted value Y. Additionally, the path that is traversed between steady-state value changes.
摘要翻译：在预测，控制和优化环境中提供独立的静态和动态模型的方法使用独立的静态模型（20）和独立的动态模型（22）。静态模型（20）是一种严格的预测模型，可在广泛的数据范围内进行训练，而动态模型（22）则是在窄范围的数据上进行训练。使用静态模型（20）的增益K来缩放动态模型（22）的增益k。被称为双变量的模型（22）的强制动态部分通过增益K和k的比率来缩放。 bi对动态模型的获得有直接的影响（22）。这通过系数修改块（40）来促进。此后，将输入到静态模型（20）的新值与先前稳态值之间的差用作动态模型（22）的输入。然后将预测的动态输出与先前的稳态值相加以提供预测值Y.此外，在稳态值变化之间经过的路径。

15. 发明申请

US20060020352A1 KILN THERMAL AND COMBUSTION CONTROL 失效
标题翻译：灼热和燃烧控制
公开(公告)号：US20060020352A1
公开(公告)日：2006-01-26
申请号：US11234927
申请日：2005-09-26
申请人： Gregory Martin , Eugene Boe , Stephen Piche , James Keeler , Douglas Timmer , Mark Gerules , John Havener
发明人： Gregory Martin , Eugene Boe , Stephen Piche , James Keeler , Douglas Timmer , Mark Gerules , John Havener
IPC分类号： G05B13/02
CPC分类号： G05B13/048 , G05B13/042 , G05B17/02
摘要： A method and apparatus for controlling a non-linear mill. A linear controller is provided having a linear gain k that is operable to receive inputs representing measured variables of the plant and predict on an output of the linear controller predicted control values for manipulatible variables that control the plant. A non-linear model of the plant is provided for storing a representation of the plant over a trained region of the operating input space and having a steady-state gain K associated therewith. The gain k of the linear model is adjusted with the gain K of the non-linear model in accordance with a predetermined relationship as the measured variables change the operating region of the input space at which the linear controller is predicting the values for the manipulatible variables. The predicted manipulatible variables are then output after the step of adjusting the gain k.
摘要翻译：一种用于控制非线性磨机的方法和装置。提供具有线性增益k的线性控制器，其可操作以接收表示工厂的测量变量的输入，并且对线控制器的输出预测控制工厂的操纵性变量的预测控制值。提供工厂的非线性模型，用于在工作输入空间的经过训练的区域上存储工厂的表示，并具有与其相关联的稳态增益K. 线性模型的增益k根据预定的关系用非线性模型的增益K进行调整，因为测量的变量改变了线性控制器预测操作变量的值的输入空间的操作区域。然后在调整增益k的步骤之后输出预测的操纵变量。

16. 发明申请

US20130055021A1 METHOD AND APPARATUS FOR MINIMIZING ERROR IN DYNAMIC AND STEADY-STATE PROCESSES FOR PREDICTION, CONTROL, AND OPTIMIZATION 审中-公开
标题翻译：用于最小化用于预测，控制和优化的动态和稳态过程中的错误的方法和装置
公开(公告)号：US20130055021A1
公开(公告)日：2013-02-28
申请号：US13608578
申请日：2012-09-10
申请人： Eugene Boe , Stephen Piche , Gregory D. Martin
发明人： Eugene Boe , Stephen Piche , Gregory D. Martin
IPC分类号： G06F11/07
CPC分类号： G05B13/027 , G05B13/042 , G05B13/048 , G05B17/02 , G09B23/02
摘要： A method for providing independent static and dynamic models in a prediction, control and optimization environment utilizes an independent static model (20) and an independent dynamic model (22). The static model (20) is a rigorous predictive model that is trained over a wide range of data, whereas the dynamic model (22) is trained over a narrow range of data. The gain K of the static model (20) is utilized to scale the gain k of the dynamic model (22). The forced dynamic portion of the model (22) referred to as the bi variables are scaled by the ratio of the gains K and k. Thereafter, the difference between the new value input to the static model (20) and the prior steady-state value is utilized as an input to the dynamic model (22). The predicted dynamic output is then summed with the previous steady-state value to provide a predicted value Y.
摘要翻译：在预测，控制和优化环境中提供独立的静态和动态模型的方法使用独立的静态模型（20）和独立的动态模型（22）。静态模型（20）是一种严格的预测模型，可在广泛的数据范围内进行训练，而动态模型（22）则是在窄范围的数据上进行训练。使用静态模型（20）的增益K来缩放动态模型（22）的增益k。被称为双变量的模型（22）的强制动态部分通过增益K和k的比率来缩放。此后，将输入到静态模型（20）的新值与先前稳态值之间的差用作动态模型（22）的输入。然后将预测的动态输出与先前的稳态值相加以提供预测值Y.

17. 发明授权

US07610108B2 Method and apparatus for attenuating error in dynamic and steady-state processes for prediction, control, and optimization 有权
标题翻译：用于衰减动态和稳态过程误差的方法和装置，用于预测，控制和优化
公开(公告)号：US07610108B2
公开(公告)日：2009-10-27
申请号：US11359295
申请日：2006-02-21
申请人： Eugene Boe , Stephen Piche , Gregory D. Martin
发明人： Eugene Boe , Stephen Piche , Gregory D. Martin
IPC分类号： G05B13/02
CPC分类号： G05B13/042 , G05B13/027 , G05B13/048
摘要： A method for providing independent static and dynamic models in a prediction, control and optimization environment utilizes an independent static model (20) and an independent dynamic model (22). The static model (20) is a rigorous predictive model that is trained over a wide range of data, whereas the dynamic model (22) is trained over a narrow range of data. The gain K of the static model (20) is utilized to scale the gain k of the dynamic model (22). The forced dynamic portion of the model (22) referred to as the bi variables are scaled by the ratio of the gains K and k. The bi have a direct effect on the gain of a dynamic model (22). This is facilitated by a coefficient modification block (40). Thereafter, the difference between the new value input to the static model (20) and the prior steady-state value is utilized as an input to the dynamic model (22). The predicted dynamic output is then summed with the previous steady-state value to provide a predicted value Y. Additionally, the path that is traversed between steady-state value changes.
摘要翻译：在预测，控制和优化环境中提供独立的静态和动态模型的方法使用独立的静态模型（20）和独立的动态模型（22）。静态模型（20）是一种严格的预测模型，可在广泛的数据范围内进行训练，而动态模型（22）则是在窄范围的数据上进行训练。使用静态模型（20）的增益K来缩放动态模型（22）的增益k。被称为双变量的模型（22）的强制动态部分通过增益K和k的比率来缩放。 bi对动态模型的获得有直接的影响（22）。这通过系数修改块（40）来促进。此后，将输入到静态模型（20）的新值与先前稳态值之间的差用作动态模型（22）的输入。然后将预测的动态输出与先前的稳态值相加以提供预测值Y.此外，在稳态值变化之间经过的路径。

18. 发明授权

US07418301B2 Method and apparatus for approximating gains in dynamic and steady-state processes for prediction, control, and optimization 有权
标题翻译：用于逼近动态和稳态过程中用于预测，控制和优化的增益的方法和装置
公开(公告)号：US07418301B2
公开(公告)日：2008-08-26
申请号：US11359114
申请日：2006-02-21
申请人： Eugene Boe , Stephen Piche , Gregory D. Martin
发明人： Eugene Boe , Stephen Piche , Gregory D. Martin
IPC分类号： G05B13/02
CPC分类号： G05B13/042 , G05B13/048
摘要： A method and apparatus for controlling a non-linear mill. A linear controller is provided having a linear gain k that is operable to receive inputs representing measured variables of the plant and predict on an output of the linear controller predicted control values for manipulatible variables that control the plant. A non-linear model of the plant is provided for storing a representation of the plant over a trained region of the operating input space and having a steady-state gain K associated therewith. The gain k of the linear model is adjusted with the gain K of the non-linear model in accordance with a predetermined relationship as the measured variables change the operating region of the input space at which the linear controller is predicting the values for the manipulatible variables. The predicted manipulatible variables are then output after the step of adjusting the gain k.
摘要翻译：一种用于控制非线性磨机的方法和装置。提供具有线性增益k的线性控制器，其可操作以接收表示工厂的测量变量的输入，并且对线性控制器的输出预测用于控制工厂的操纵性变量的预测控制值。提供工厂的非线性模型，用于在工作输入空间的经过训练的区域上存储工厂的表示，并具有与其相关联的稳态增益K. 线性模型的增益k根据预定的关系用非线性模型的增益K进行调整，因为测量的变量改变了线性控制器预测操作变量的值的输入空间的操作区域。然后在调整增益k的步骤之后输出预测的操纵变量。

19. 发明授权

US09329582B2 Method and apparatus for minimizing error in dynamic and steady-state processes for prediction, control, and optimization 有权
标题翻译：用于最小化用于预测，控制和优化的动态和稳态过程中的误差的方法和装置
公开(公告)号：US09329582B2
公开(公告)日：2016-05-03
申请号：US13608578
申请日：2012-09-10
申请人： Eugene Boe , Stephen Piche , Gregory D. Martin
发明人： Eugene Boe , Stephen Piche , Gregory D. Martin
IPC分类号： G05B9/02 , G05B13/02 , G05B13/04 , G05B17/02
CPC分类号： G05B13/027 , G05B13/042 , G05B13/048 , G05B17/02 , G09B23/02
摘要： A method for providing independent static and dynamic models in a prediction, control and optimization environment utilizes an independent static model (20) and an independent dynamic model (22). The static model (20) is a rigorous predictive model that is trained over a wide range of data, whereas the dynamic model (22) is trained over a narrow range of data. The gain K of the static model (20) is utilized to scale the gain k of the dynamic model (22). The forced dynamic portion of the model (22) referred to as the bi variables are scaled by the ratio of the gains K and k. Thereafter, the difference between the new value input to the static model (20) and the prior steady-state value is utilized as an input to the dynamic model (22). The predicted dynamic output is then summed with the previous steady-state value to provide a predicted value Y.
摘要翻译：在预测，控制和优化环境中提供独立的静态和动态模型的方法使用独立的静态模型（20）和独立的动态模型（22）。静态模型（20）是一种严格的预测模型，可在广泛的数据范围内进行训练，而动态模型（22）则是在窄范围的数据上进行训练。使用静态模型（20）的增益K来缩放动态模型（22）的增益k。被称为双变量的模型（22）的强制动态部分通过增益K和k的比率来缩放。此后，将输入到静态模型（20）的新值与先前稳态值之间的差用作动态模型（22）的输入。然后将预测的动态输出与先前的稳态值相加以提供预测值Y.

20. 发明授权

US08311673B2 Method and apparatus for minimizing error in dynamic and steady-state processes for prediction, control, and optimization 有权
标题翻译：用于最小化用于预测，控制和优化的动态和稳态过程中的误差的方法和装置
公开(公告)号：US08311673B2
公开(公告)日：2012-11-13
申请号：US11359296
申请日：2006-02-21
申请人： Eugene Boe , Stephen Piche , Gregory D. Martin
发明人： Eugene Boe , Stephen Piche , Gregory D. Martin
IPC分类号： G05B19/04 , G06F19/00
CPC分类号： G05B13/027 , G05B13/042 , G05B13/048 , G05B17/02 , G09B23/02
摘要： A method for providing independent static and dynamic models in a prediction, control and optimization environment utilizes an independent static model (20) and an independent dynamic model (22). The static model (20) is a rigorous predictive model that is trained over a wide range of data, whereas the dynamic model (22) is trained over a narrow range of data. The gain K of the static model (20) is utilized to scale the gain k of the dynamic model (22). The forced dynamic portion of the model (22) referred to as the bi variables are scaled by the ratio of the gains K and k. Thereafter, the difference between the new value input to the static model (20) and the prior steady-state value is utilized as an input to the dynamic model (22). The predicted dynamic output is then summed with the previous steady-state value to provide a predicted value Y.
摘要翻译：在预测，控制和优化环境中提供独立的静态和动态模型的方法使用独立的静态模型（20）和独立的动态模型（22）。静态模型（20）是一种严格的预测模型，可在广泛的数据范围内进行训练，而动态模型（22）则是在窄范围的数据上进行训练。使用静态模型（20）的增益K来缩放动态模型（22）的增益k。被称为双变量的模型（22）的强制动态部分通过增益K和k的比率来缩放。此后，将输入到静态模型（20）的新值与先前稳态值之间的差用作动态模型（22）的输入。然后将预测的动态输出与先前的稳态值相加以提供预测值Y.

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