公开(公告)号：US10018997B2

公开(公告)日：2018-07-10

申请号：US13931341

申请日：2013-06-28

Applicant: Christopher J. Worek ,  Terrence L. Blevins ,  Robert B. Havekost ,  Dirk Thiele

Inventor： Christopher J. Worek ,  Terrence L. Blevins ,  Robert B. Havekost ,  Dirk Thiele

IPC: G05B13/04 ,  G05B19/418

CPC classification number: G05B19/41885 ,  G05B2219/31357 ,  G05B2219/31472 ,  Y02P90/14 ,  Y02P90/22 ,  Y02P90/26

Abstract: An on-line data analytics device can be installed in a process control system as a standalone device that operates in parallel with, but non-intrusively with respect to, the on-line control system to perform on-line analytics for a process without requiring the process control system to be reconfigured or recertified. The data analytics device includes a data analytics engine coupled to a logic engine that receives process data collected from the process control system in a non-intrusive manner. The logic engine operates to determine further process variable values not generated within the process control system and provides the collected process variable data and the further process variable values to the data analytics engine. The data analytics engine executes statistically based process models, such as batch models, stage models, and phase models, to produce a predicted process variable, such as an end of stage or end of batch quality variable for use in analyzing the operation of the on-line process.

公开(公告)号：US20120209557A1

公开(公告)日：2012-08-16

申请号：US13025441

申请日：2011-02-11

Applicant: Brian Crandall ,  Dirk Thiele ,  Noel Bell

Inventor： Brian Crandall ,  Dirk Thiele ,  Noel Bell

IPC: G06F19/00

CPC classification number: G05B19/41885 ,  G05B2219/32364 ,  Y02P90/20 ,  Y02P90/26

Abstract: Example methods, apparatus and articles to test batch configurations are disclosed. A disclosed example method includes identifying, using a processor, an execution path through a batch configuration of a process control system, generating a test plan for the execution path, stimulating the process control system to execute the test plan, and recording a result of the test plan.

Abstract translation: 公开了用于测试批量配置的示例性方法，设备和制品。 所公开的示例性方法包括通过处理控制系统的批量配置来识别使用处理器的执行路径，生成用于执行路径的测试计划，刺激过程控制系统执行测试计划，以及记录 测试计划。

公开(公告)号：US07856281B2

公开(公告)日：2010-12-21

申请号：US12267039

申请日：2008-11-07

Applicant: Dirk Thiele ,  Wilhelm K. Wojsznis

Inventor： Dirk Thiele ,  Wilhelm K. Wojsznis

IPC: G05B13/02

CPC classification number: G05B13/048

Abstract: A method of creating and using an adaptive DMC type or other MPC controller includes using a model switching technique to periodically determine a process model, such as a parameterized process model, for a process loop on-line during operation of the process. The method then uses the process model to generate an MPC control model and creates and downloads an MPC controller algorithm to an MPC controller based on the new control model while the MPC controller is operating on-line. This technique, which is generally applicable to single-loop MPC controllers and is particularly useful in MPC controllers with a control horizon of one or two, enables an MPC controller to be adapted during the normal operation of the process, so as to change the process model on which the MPC controller is based to thereby account for process changes. The adaptive MPC controller is not computationally expensive and can therefore be easily implemented within a distributed controller of a process control system, while providing the same or in some cases better control than a PID controller, especially in dead time dominant process loops, and in process loops that are subject to process model mismatch within the process time to steady state.

Abstract translation: 创建和使用自适应DMC类型或其他MPC控制器的方法包括使用模型切换技术来周期性地确定过程模型，例如参数化过程模型，用于在过程操作期间在线的过程循环。 然后，该方法使用过程模型来生成MPC控制模型，并且在MPC控制器在线运行时，基于新的控制模型创建MPC控制器算法并将其下载到MPC控制器。 这种技术通常适用于单回路MPC控制器，并且在控制范围为1或2的MPC控制器中特别有用，可以在过程的正常运行期间调整MPC控制器，以便改变过程 MPC控制器所基于的模型，从而说明过程变化。 自适应MPC控制器在计算上不是昂贵的，因此可以容易地在过程控制系统的分布式控制器内实现，同时提供与PID控制器相同或在某些情况下比PID控制器更好的控制，特别是在死区时间主流过程循环中，并且在处理过程中 在处理时间内处于稳定状态的流程模型不匹配的循环。

公开(公告)号：US07840287B2

公开(公告)日：2010-11-23

申请号：US11403361

申请日：2006-04-13

Applicant: Wilhelm K. Wojsznis ,  Ashish Mehta ,  Dirk Thiele

Inventor： Wilhelm K. Wojsznis ,  Ashish Mehta ,  Dirk Thiele

IPC: G05B13/02 ,  G05B11/01 ,  G06F19/00 ,  G06F11/30 ,  G06F7/60 ,  G06F17/10 ,  G21C17/00 ,  H03F1/26 ,  H04B15/00

CPC classification number: G05B13/048 ,  G05B17/02

Abstract: A robust method of creating process models for use in controller generation, such as in MPC controller generation, adds noise to the process data collected and used in the model generation process. In particular, a robust method of creating a parametric process model first collects process outputs based on known test input signals or sequences, adds random noise to the collected process data and then uses a standard or known technique to determine a process model from the collected process data. Unlike existing techniques for noise removal that focus on clean up of non-random noise prior to generating a process model, the addition of random, zero-mean noise to the process data enables, in many cases, the generation of an acceptable parametric process model in situations where no process model parameter convergence was otherwise obtained. Additionally, process models created using this technique generally have wider confidence intervals, therefore providing a model that works adequately in many process situations without needing to manually or graphically change the model.

Abstract translation: 创建用于控制器生成过程模型（例如MPC控制器生成）的可靠方法为模型生成过程中收集和使用的过程数据增加了噪音。 特别地，创建参数过程模型的可靠方法首先基于已知的测试输入信号或序列收集过程输出，将随机噪声添加到收集的过程数据，然后使用标准或已知技术从收集的过程中确定过程模型 数据。 与在生成过程模型之前关注清除非随机噪声的噪声去除技术不同，在过程数据中添加随机的零均值噪声能够在许多情况下产生可接受的参数过程模型 在没有获得过程模型参数收敛的情况下。 此外，使用此技术创建的过程模型通常具有更宽的置信区间，因此提供了一个可在许多过程情况下正常工作的模型，无需手动或图形地更改模型。

公开(公告)号：US20090198350A1

公开(公告)日：2009-08-06

申请号：US12363305

申请日：2009-01-30

Applicant: Dirk Thiele

Inventor： Dirk Thiele

IPC: G05B13/04 ,  G05B15/02 ,  G06F3/048 ,  G06N5/02

CPC classification number: G05B13/042 ,  G05B13/048 ,  G05B17/02

Abstract: An MPC adaptation and tuning technique integrates feedback control performance better than methods commonly used today in MPC type controllers, resulting in an MPC adaptation/tuning technique that performs better than traditional MPC techniques in the presence of process model mismatch. The MPC controller performance is enhanced by adding a controller adaptation/tuning unit to an MPC controller, which adaptation/tuning unit implements an optimization routine to determine the best or most optimal set of controller design and/or tuning parameters to use within the MPC controller during on-line process control in the presence of a specific amount of model mismatch or a range of model mismatch. The adaptation/tuning unit determines one or more MPC controller tuning and design parameters, including for example, an MPC form, penalty factors for either or both of an MPC controller and an observer and a controller model for use in the MPC controller, based on a previously determined process model and either a known or an expected process model mismatch or process model mismatch range. A closed loop adaptation cycle may be implemented by performing an autocorrelation analysis on the prediction error or the control error to determine when significant process model mismatch exists or to determine an increase or a decrease in process model mismatch over time.

Abstract translation: MPC适配和调谐技术将反馈控制性能与MPC型控制器当今通常使用的方法相比较，结果是MPC适配/调谐技术在传统的MPC技术存在过程模型不匹配的情况下表现更好。 通过向MPC控制器添加控制器自适应/调谐单元来增强MPC控制器性能，该适配/调谐单元执行优化程序，以确定在MPC控制器内使用的最佳或最优化的控制器设计和/或调谐参数集 在存在特定量的模型不匹配或模型不匹配范围的在线过程控制期间。 适配/调谐单元确定一个或多个MPC控制器调谐和设计参数，包括例如MPC形式，用于MPC控制器和观察者中的任一者或两者的惩罚因子以及用于MPC控制器中的控制器模型，基于 先前确定的过程模型以及已知或预期的过程模型失配或过程模型不匹配范围。 可以通过对预测误差或控制误差进行自相关分析来确定闭环适配周期，以确定何时存在显着的过程模型不匹配或者确定过程模型不匹配随时间的增加或减少。

公开(公告)号：US07451004B2

公开(公告)日：2008-11-11

申请号：US11240705

申请日：2005-09-30

Applicant: Dirk Thiele ,  Wilhelm K. Wojsznis

Inventor： Dirk Thiele ,  Wilhelm K. Wojsznis

IPC: G05B13/02

CPC classification number: G05B13/048

Abstract: A method of creating and using an adaptive DMC type or other MPC controller includes using a model switching technique to periodically determine a process model, such as a parameterized process model, for a process loop on-line during operation of the process. The method then uses the process model to generate an MPC control model and creates and downloads an MPC controller algorithm to an MPC controller based on the new control model while the MPC controller is operating on-line. This technique, which is generally applicable to single-loop MPC controllers and is particularly useful in MPC controllers with a control horizon of one or two, enables an MPC controller to be adapted during the normal operation of the process, so as to change the process model on which the MPC controller is based to thereby account for process changes. The adaptive MPC controller is not computationally expensive and can therefore be easily implemented within a distributed controller of a process control system, while providing the same or in some cases better control than a PID controller, especially in dead time dominant process loops, and in process loops that are subject to process model mismatch within the process time to steady state.

Abstract translation: 创建和使用自适应DMC类型或其他MPC控制器的方法包括使用模型切换技术来周期性地确定过程模型，例如参数化过程模型，用于在过程操作期间在线的过程循环。 然后，该方法使用过程模型来生成MPC控制模型，并且在MPC控制器在线运行时，基于新的控制模型创建MPC控制器算法并将其下载到MPC控制器。 这种技术通常适用于单回路MPC控制器，并且在控制范围为1或2的MPC控制器中特别有用，可以在过程的正常运行期间调整MPC控制器，以便改变过程 MPC控制器所基于的模型，从而说明过程变化。 自适应MPC控制器在计算上不是昂贵的，因此可以容易地在过程控制系统的分布式控制器内实现，同时提供与PID控制器相同或在某些情况下比PID控制器更好的控制，特别是在死区时间主导过程循环中，并且在处理中 在处理时间内处于稳定状态的流程模型不匹配的循环。

公开(公告)号：US06847954B1

公开(公告)日：2005-01-25

申请号：US09644399

申请日：2000-08-23

Applicant: Wilhelm K. Wojsznis ,  Terrence L. Blevins ,  Dirk Thiele

Inventor： Wilhelm K. Wojsznis ,  Terrence L. Blevins ,  Dirk Thiele

IPC: G05B13/02 ,  G05G7/00 ,  G05E1/00 ,  G05E3/00 ,  G05F15/18

CPC classification number: G05B13/0285

Abstract: A system for tuning a process control loop includes a tuner module for receiving an error signal representative of the difference between a set point and a process variable, the module generating a first process control signal for controlling the process. The system further includes a controller module for receiving the error signal and a parameter signal from a nonlinear module to generate a second process control signal for controlling the process, wherein the nonlinear module applies a nonlinear procedure to generate the parameter signal. The system further includes a switching means coupled to the tuner module and the controller module to select the appropriate process control signal for controlling the process. The system provided uses nonlinear techniques in the nonlinear module to approximate the desired controller tuning parameters. The nonlinear techniques include neural network tuning, fuzzy logic tuning and nonlinear functions, including sigmoid tuning. A system also provides that the nonlinear module use nonlinear techniques to approximate the desired process model parameters. According to an embodiment of the present invention, the nonlinear module includes a process model identification module and a controller tuning module that provides controller parameters and model identification parameters using neural networks, fuzzy logic and nonlinear functions, including sigmoid tuning.

Abstract translation: 用于调整过程控制回路的系统包括调谐器模块，用于接收表示设定点和过程变量之间的差异的误差信号，该模块产生用于控制过程的第一过程控制信号。 该系统还包括控制器模块，用于从非线性模块接收误差信号和参数信号，以生成用于控制过程的第二过程控制信号，其中非线性模块应用非线性过程来产生参数信号。 该系统还包括耦合到调谐器模块和控制器模块的切换装置，以选择用于控制该过程的适当的过程控制信号。 所提供的系统在非线性模块中使用非线性技术来近似所需的控制器调谐参数。 非线性技术包括神经网络调谐，模糊逻辑调谐和非线性函数，包括S形调谐。 系统还提供非线性模块使用非线性技术近似所需的过程模型参数。 根据本发明的实施例，非线性模块包括过程模型识别模块和控制器调谐模块，其使用神经网络，模糊逻辑和非线性函数提供控制器参数和模型识别参数，包括S形调谐。

公开(公告)号：US20120221124A1

公开(公告)日：2012-08-30

申请号：US13465764

申请日：2012-05-07

Applicant: Dirk Thiele

Inventor： Dirk Thiele

IPC: G05B13/04

CPC classification number: G05B13/042 ,  G05B13/048 ,  G05B17/02

Abstract: A process controller adaptation and tuning technique uses a closed loop adaptation cycle that performs an autocorrelation analysis on the prediction error or the control error of a process control system to determine if significant process model mismatch exists or to determine an increase or a decrease in process model mismatch over time. The adaptation and tuning technique may perform a controller tuning cycle when the determined model mismatch raises above a predetermined level.

Abstract translation: 过程控制器适配和调整技术使用闭环适配周期，其对过程控制系统的预测误差或控制误差执行自相关分析，以确定是否存在显着的过程模型不匹配或确定过程模型的增加或减少 随着时间的推移不匹配 当所确定的模型失配升高到高于预定水平时，适配和调谐技术可以执行控制器调谐周期。

公开(公告)号：US20150005903A1

公开(公告)日：2015-01-01

申请号：US13931341

申请日：2013-06-28

Applicant: Christopher J. Worek ,  Terrence L. Blevins ,  Robert B. Havekost ,  Dirk Thiele

Inventor： Christopher J. Worek ,  Terrence L. Blevins ,  Robert B. Havekost ,  Dirk Thiele

IPC: G05B13/04

CPC classification number: G05B19/41885 ,  G05B2219/31357 ,  G05B2219/31472 ,  Y02P90/14 ,  Y02P90/22 ,  Y02P90/26

Abstract: An on-line data analytics device can be installed in a process control system as a standalone device that operates in parallel with, but non-intrusively with respect to, the on-line control system to perform on-line analytics for a process without requiring the process control system to be reconfigured or recertified. The data analytics device includes a data analytics engine coupled to a logic engine that receives process data collected from the process control system in a non-intrusive manner. The logic engine operates to determine further process variable values not generated within the process control system and provides the collected process variable data and the further process variable values to the data analytics engine. The data analytics engine executes statistically based process models, such as batch models, stage models, and phase models, to produce a predicted process variable, such as an end of stage or end of batch quality variable for use in analyzing the operation of the on-line process.

Abstract translation: 在线数据分析设备可以作为独立设备安装在过程控制系统中，该设备与在线控制系统并行运行，但是非侵入式地在线控制系统上进行流程的在线分析，而不需要 要重新配置或重新认证的过程控制系统。 数据分析设备包括耦合到逻辑引擎的数据分析引擎，其以非侵入方式接收从过程控制系统收集的过程数据。 逻辑引擎操作以确定在过程控制系统内未生成的另外的过程变量值，并将收集的过程变量数据和进一步的过程变量值提供给数据分析引擎。 数据分析引擎执行基于统计的过程模型，例如批量模型，阶段模型和阶段模型，以产生预测的过程变量，例如用于分析操作的批次质量变量的阶段或结束的结束 线程过程

公开(公告)号：US08788239B2

公开(公告)日：2014-07-22

申请号：US13025441

申请日：2011-02-11

Applicant: Brian Crandall ,  Dirk Thiele ,  Noel Bell

Inventor： Brian Crandall ,  Dirk Thiele ,  Noel Bell

IPC: G06F19/00 ,  G05B21/00 ,  G06F7/00

CPC classification number: G05B19/41885 ,  G05B2219/32364 ,  Y02P90/20 ,  Y02P90/26

Abstract: Example methods, apparatus and articles to test batch configurations are disclosed. A disclosed example method includes identifying, using a processor, an execution path through a batch configuration of a process control system, generating a test plan for the execution path, stimulating the process control system to execute the test plan, and recording a result of the test plan.

Abstract translation: 公开了用于测试批量配置的示例性方法，设备和制品。 所公开的示例性方法包括通过处理控制系统的批量配置来识别使用处理器的执行路径，生成用于执行路径的测试计划，刺激过程控制系统执行测试计划，以及记录 测试计划。