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    • 11. 发明申请
    • Robust process model identification in model based control techniques
    • 基于模型的控制技术的鲁棒过程模型识别
    • US20070244575A1
    • 2007-10-18
    • US11403361
    • 2006-04-13
    • Wilhelm WojsznisAshish MehtaDirk Thiele
    • Wilhelm WojsznisAshish MehtaDirk Thiele
    • G05B13/02
    • G05B13/048G05B17/02
    • 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.
    • 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。
    • 13. 发明授权
    • On-line adaptive model predictive control in a process control system
    • 过程控制系统中的在线自适应模型预测控制
    • US07856281B2
    • 2010-12-21
    • US12267039
    • 2008-11-07
    • Dirk ThieleWilhelm K. Wojsznis
    • Dirk ThieleWilhelm K. Wojsznis
    • G05B13/02
    • G05B13/048
    • 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.
    • 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。
    • 14. 发明授权
    • Robust process model identification in model based control techniques
    • 基于模型的控制技术的鲁棒过程模型识别
    • US07840287B2
    • 2010-11-23
    • US11403361
    • 2006-04-13
    • Wilhelm K. WojsznisAshish MehtaDirk Thiele
    • Wilhelm K. WojsznisAshish MehtaDirk Thiele
    • G05B13/02G05B11/01G06F19/00G06F11/30G06F7/60G06F17/10G21C17/00H03F1/26H04B15/00
    • G05B13/048G05B17/02
    • 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.
    • 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。
    • 15. 发明申请
    • ROBUST ADAPTIVE MODEL PREDICTIVE CONTROLLER WITH TUNING TO COMPENSATE FOR MODEL MISMATCH
    • 鲁棒自适应模型预测控制器,具有调谐补偿模型误差
    • US20090198350A1
    • 2009-08-06
    • US12363305
    • 2009-01-30
    • Dirk Thiele
    • Dirk Thiele
    • G05B13/04G05B15/02G06F3/048G06N5/02
    • G05B13/042G05B13/048G05B17/02
    • 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.
    • 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。
    • 16. 发明授权
    • On-line adaptive model predictive control in a process control system
    • 过程控制系统中的在线自适应模型预测控制
    • US07451004B2
    • 2008-11-11
    • US11240705
    • 2005-09-30
    • Dirk ThieleWilhelm K. Wojsznis
    • Dirk ThieleWilhelm K. Wojsznis
    • G05B13/02
    • G05B13/048
    • 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.
    • 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。
    • 18. 发明授权
    • Model predictive controller with tunable integral component to compensate for model mismatch
    • 具有可调谐积分分量的模型预测控制器,用于补偿模型不匹配
    • US08200346B2
    • 2012-06-12
    • US12698991
    • 2010-02-02
    • Dirk Thiele
    • Dirk Thiele
    • G05B13/02
    • G05B17/02
    • An MPC controller technique integrates feedback control performance better than methods commonly used today in MPC type controllers, resulting in an MPC controller that performs better than traditional MPC techniques in the presence of process model mismatch. In particular, MPC controller performance is enhanced by adding a tunable integration block to the MPC controller that develops an integral component indicative of the prediction or other control error, and adds this component to the output of an MPC controller algorithm to provide for faster or better control in the presence of model mismatch, which is the ultimate reason for the prediction error in the first place. This technique enables the MPC controller to react more quickly and to provide better set point change and load disturbance performance in the presence of model mismatch, without decreasing the robustness of the MPC controller.
    • MPC控制器技术将反馈控制性能优于MPC型控制器当今通常使用的方法,从而在存在过程模型不匹配的情况下,MPC控制器的性能优于传统MPC技术。 特别地,MPC控制器性能通过向MPC控制器添加可调整积分块来增强,该MPC控制器开发指示预测或其他控制误差的积分分量,并将该组件添加到MPC控制器算法的输出以提供更快或更好的 在存在模型不匹配的情况下进行控制,这是预测误差的最终原因。 这种技术使得MPC控制器能够更快地作出反应,并在存在模型不匹配的情况下提供更好的设定点变化和负载干扰性能,而不会降低MPC控制器的鲁棒性。
    • 19. 发明申请
    • METHODS, APPARATUS AND ARTICLES OF MANUFACTURE TO TEST PROCESS CONTROL SYSTEMS
    • 方法,制造与测试过程控制系统的装置和文章
    • US20120046764A1
    • 2012-02-23
    • US12861515
    • 2010-08-23
    • Tom AneweerDirk ThieleNoel Bell
    • Tom AneweerDirk ThieleNoel Bell
    • G05B9/02
    • G05B23/0237
    • Example methods, apparatus and articles of manufacture to test process control systems are disclosed. A disclosed example method includes obtaining user inputs to a first process control system, obtaining process inputs and first process outputs of the first process control system, providing the user inputs and the process inputs to a second process control system to operate the second process control system, obtaining second process outputs of the second process control system operated with the user inputs and the process inputs, and comparing the first and second process outputs to determine whether the second process control system is implemented as intended.
    • 公开了用于测试过程控制系统的示例性方法,设备和制品。 所公开的示例性方法包括获得第一过程控制系统的用户输入,获得第一过程控制系统的过程输入和第一处理输出,向第二过程控制系统提供用户输入和过程输入以操作第二过程控制系统 获得用用户输入和过程输入操作的第二过程控制系统的第二过程输出,以及比较第一和第二过程输出,以确定第二过程控制系统是否按预期实现。