公开(公告)号：US07330804B2

公开(公告)日：2008-02-12

申请号：US09892586

申请日：2001-06-27

申请人： Paul Turner ,  John P. Guiver ,  Brian Lines ,  S. Steven Treiber

发明人： Paul Turner ,  John P. Guiver ,  Brian Lines ,  S. Steven Treiber

IPC分类号： G06F7/60 ,  G06F17/10 ,  G06F15/18 ,  G05B13/02 ,  G06E1/00 ,  G06E3/00

CPC分类号： G05B13/027 ,  G05B17/02

摘要： A constrained non-linear approximator for empirical process control is disclosed. The approximator constrains the behavior of the derivative of a subject empirical model without adversely affecting the ability of the model to represent generic non-linear relationships. There are three stages to developing the constrained non-linear approximator. The first stage is the specification of the general shape of the gain trajectory or base non-linear function which is specified graphically, algebraically or generically and is used as the basis for transfer functions used in the second stage. The second stage of the invention is the interconnection of the transfer functions to allow non-linear approximation. The final stage of the invention is the constrained optimization of the model coefficients such that the general shape of the input/output mappings (and their corresponding derivatives) are conserved.

摘要翻译： 公开了用于经验过程控制的约束非线性近似器。 近似器约束主体经验模型的导数的行为，而不会对模型表示通用非线性关系的能力产生不利影响。 开发约束非线性近似器有三个阶段。 第一阶段是以图形，代数或一般的方式指定的增益轨迹或基础非线性函数的一般形状的规范，并用作第二阶段中使用的传递函数的基础。 本发明的第二阶段是传递函数的互连以允许非线性近似。 本发明的最后阶段是模型系数的约束优化，使得输入/输出映射（及其相应的导数）的一般形状被保守。

公开(公告)号：US08296107B2

公开(公告)日：2012-10-23

申请号：US12615754

申请日：2009-11-10

申请人： Paul Turner ,  John P. Guiver ,  Brian Lines ,  S. Steven Treiber

发明人： Paul Turner ,  John P. Guiver ,  Brian Lines ,  S. Steven Treiber

IPC分类号： G06F17/10

CPC分类号： G05B13/027 ,  G05B17/02

摘要： A constrained non-linear approximator for empirical process control is disclosed. The approximator constrains the behavior of the derivative of a subject empirical model without adversely affecting the ability of the model to represent generic non-linear relationships. There are three stages to developing the constrained non-linear approximator. The first stage is the specification of the general shape of the gain trajectory or base non-linear function which is specified graphically, algebraically or generically and is used as the basis for transfer functions used in the second stage. The second stage of the invention is the interconnection of the transfer functions to allow non-linear approximation. The final stage of the invention is the constrained optimization of the model coefficients such that the general shape of the input/output mappings (and their corresponding derivatives) are conserved.

摘要翻译： 公开了用于经验过程控制的约束非线性近似器。 近似器约束主体经验模型的导数的行为，而不会不利地影响模型表示通用非线性关系的能力。 开发约束非线性近似器有三个阶段。 第一阶段是以图形，代数或一般的方式指定的增益轨迹或基础非线性函数的一般形状的规范，并用作第二阶段中使用的传递函数的基础。 本发明的第二阶段是传递函数的互连以允许非线性近似。 本发明的最后阶段是模型系数的约束优化，使得输入/输出映射（及其相应的导数）的一般形状被保守。

公开(公告)号：US20100057222A1

公开(公告)日：2010-03-04

申请号：US12615754

申请日：2009-11-10

申请人： Paul Turner ,  John P. Guiver ,  Brian Lines ,  S. Steven Treiber

发明人： Paul Turner ,  John P. Guiver ,  Brian Lines ,  S. Steven Treiber

IPC分类号： G05B13/04 ,  G06F17/11 ,  G06F15/18

CPC分类号： G05B13/027 ,  G05B17/02

摘要： A constrained non-linear approximator for empirical process control is disclosed. The approximator constrains the behavior of the derivative of a subject empirical model without adversely affecting the ability of the model to represent generic non-linear relationships. There are three stages to developing the constrained non-linear approximator. The first stage is the specification of the general shape of the gain trajectory or base non-linear function which is specified graphically, algebraically or generically and is used as the basis for transfer functions used in the second stage. The second stage of the invention is the interconnection of the transfer functions to allow non-linear approximation. The final stage of the invention is the constrained optimization of the model coefficients such that the general shape of the input/output mappings (and their corresponding derivatives) are conserved.

摘要翻译： 公开了用于经验过程控制的约束非线性近似器。 近似器约束主体经验模型的导数的行为，而不会不利地影响模型表示通用非线性关系的能力。 开发约束非线性近似器有三个阶段。 第一阶段是以图形，代数或一般的方式指定的增益轨迹或基础非线性函数的一般形状的规范，并用作第二阶段中使用的传递函数的基础。 本发明的第二阶段是传递函数的互连以允许非线性近似。 本发明的最后阶段是模型系数的约束优化，使得输入/输出映射（及其相应的导数）的一般形状被保守。

公开(公告)号：US07630868B2

公开(公告)日：2009-12-08

申请号：US11978320

申请日：2007-10-29

申请人： Paul Turner ,  John P. Guiver ,  Brian Lines ,  S. Steven Treiber

发明人： Paul Turner ,  John P. Guiver ,  Brian Lines ,  S. Steven Treiber

IPC分类号： G06F17/10

CPC分类号： G05B13/027 ,  G05B17/02

摘要： A constrained non-linear approximator for empirical process control is disclosed. The approximator constrains the behavior of the derivative of a subject empirical model without adversely affecting the ability of the model to represent generic non-linear relationships. There are three stages to developing the constrained non-linear approximator. The first stage is the specification of the general shape of the gain trajectory or base non-linear function which is specified graphically, algebraically or generically and is used as the basis for transfer functions used in the second stage. The second stage of the invention is the interconnection of the transfer functions to allow non-linear approximation. The final stage of the invention is the constrained optimization of the model coefficients such that the general shape of the input/output mappings (and their corresponding derivatives) are conserved.