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    • 1. 发明授权
    • Method of generating optimal control problems for industrial processes
    • 为工业过程产生最优控制问题的方法
    • US07933664B2
    • 2011-04-26
    • US11633031
    • 2006-12-04
    • Eduardo Alvarez GallesteyDario CastagnoliAlec Stothert
    • Eduardo Alvarez GallesteyDario CastagnoliAlec Stothert
    • G05B13/02
    • G05B13/042
    • Modelling of industrial processes is simplified with the use of Mixed Logical Dynamic (MLD) framework. Optimal control problems can be generated for application to industrial processes. For example, two arbitrarily connected MLD blocks are automatically merged to obtain one composite MLD block. Via a repeated use of the procedure, any arbitrarily complex system containing the complete description of an industrial process can be generated from the simplest MLD building blocks. The optimal control problem is generated via adding an MLD block whose unique output becomes the cost functional of the problem. In a graphical environment, any specific industrial process may be reproduced by instantiating blocks from a library of basic MLD elements or atomic MLD blocks and by properly connecting them. In case an appropriate library is available, this process will not require any expert knowledge from the end user apart from the ability to build the graphical interconnections mentioned.
    • 使用混合逻辑动态(MLD)框架简化了工业流程建模。 可以产生适用于工业过程的最佳控制问题。 例如,两个任意连接的MLD块被自动合并以获得一个复合MLD块。 通过重复使用该过程,可以从最简单的MLD构建块生成包含工业过程的完整描述的任何复杂的系统。 通过添加其唯一输出成为问题的成本函数的MLD块来生成最优控制问题。 在图形环境中,任何具体的工业过程可以通过从基本的MLD元素或原子MLD块的库中实例化块并通过适当地连接来再现。 在适当的库可用的情况下,除了构建所提到的图形互连的能力之外,该过程将不需要来自最终用户的任何专家知识。
    • 2. 发明授权
    • Optimal operation of a power plant
    • 发电厂的最佳运行
    • US07426456B2
    • 2008-09-16
    • US10298573
    • 2002-11-19
    • Eduardo Gallestey AlvarezAlec StothertMarc AntoineSteve Morton
    • Eduardo Gallestey AlvarezAlec StothertMarc AntoineSteve Morton
    • G06F17/10
    • G05B19/41885G05B2219/32017G05B2219/32343Y02E20/16Y02P90/26Y02P90/86
    • In a method and computer program product for optimal operation of a power plant and a power plant optimising system an optimisation mode (1) minimises a cost function (J[u],J[P]) that comprises a deviation of lifetime of plant components (LTp(τ)) from a desired nominal lifetime trajectory (LTn(τ)). This is done by, at a given time, determining future values of input values (u(τ),P(τ)) such as control values (P(τ)) or process values (u(τ)) to the plant and simulating, in a simulation modulate (2), the behaviour of the plant up to a given future time. Corresponding lifetime values are determined in the simulation, and incorporated in an objective function. The optimisation module (1) minimises the cost function (J[u],J[P]) by varying the input values (u(τ),P(τ)). As a result, it is possible to operate the plant such that component lifetime (LTp(τ)) follows the desired trajectory (LTn(τ)).
    • 在用于发电厂和发电厂优化系统的最佳运行的方法和计算机程序产品中,优化模式(1)使包括工厂部件的寿命偏差的成本函数(J [u],J [P])最小化 (LTp(τ))从期望的标称寿命轨迹(LTn(τ))。 这通过在给定时间来确定植物的输入值(u(τ),P(τ))的未来值(例如控制值(P(τ))或过程值(u(τ))) 模拟,在模拟调制(2)中,植物的行为直到给定的未来时间。 相应的寿命值在模拟中确定,并入目标函数。 优化模块(1)通过改变输入值(u(τ),P(τ))来最小化成本函数(J [u],J [P])。 因此,可以使设备操作,使得组件寿命(LTp(τ))遵循期望的轨迹(LTn(τ))。
    • 3. 发明授权
    • Process control system
    • 过程控制系统
    • US07266416B2
    • 2007-09-04
    • US11019208
    • 2004-12-23
    • Eduardo Alvarez GallesteyAlec Stothert
    • Eduardo Alvarez GallesteyAlec Stothert
    • G05B13/02
    • G05B13/048G05B13/042
    • The disclosed process control system makes use of Optimal control (OC) and model predictive control (MPC) techniques for selection of the Expert Systems (ES) targets values U. The ES target values U are selected to minimize the performance criterion J. A mathematical model of an extended system given by the process P and the ES is developed. This hybrid mathematical model has both continuous dynamics and logical relationships. Controlled variables of the mathematical model are the ES target values U and inputs are the measurements y and the performance criterion J. The OC and/or MPC techniques are used to compute values U. An optimizer of the OC/MPC selects values of the ES target values U only. This activity has lower sampling rates than selection of controller values, which simplifies the design of the OC/MPC controller.
    • 所公开的过程控制系统利用最佳控制(OC)和模型预测控制(MPC)技术来选择专家系统(ES)目标值U.ES目标值U被选择以使性能标准J最小化。数学 开发了由过程P和ES给出的扩展系统的模型。 这种混合数学模型具有连续动力学和逻辑关系。 数学模型的受控变量是ES目标值U,输入是测量y和性能标准J. OC和/或MPC技术用于计算值U. OC / MPC的优化器选择ES的值 目标值U。 该活动的采样率低于控制器值的选择,这简化了OC / MPC控制器的设计。
    • 4. 发明申请
    • Method of generating optical control problems for industrial processes
    • 产生工业过程光学控制问题的方法
    • US20070143074A1
    • 2007-06-21
    • US11633031
    • 2006-12-04
    • Eduardo GallesteyDario CastagnoliAlec Stothert
    • Eduardo GallesteyDario CastagnoliAlec Stothert
    • G06F15/00
    • G05B13/042
    • Modelling of industrial processes is simplified with the use of Mixed Logical Dynamic (MLD) framework. Optimal control problems can be generated for application to industrial processes. For example, two arbitrarily connected MLD blocks are automatically merged to obtain one composite MLD block. Via a repeated use of the procedure, any arbitrarily complex system containing the complete description of an industrial process can be generated from the simplest MLD building blocks. The optimal control problem is generated via adding an MLD block whose unique output becomes the cost functional of the problem. In a graphical environment, any specific industrial process may be reproduced by instantiating blocks from a library of basic MLD elements or atomic MLD blocks and by properly connecting them. In case an appropriate library is available, this process will not require any expert knowledge from the end user apart from the ability to build the graphical interconnections mentioned.
    • 使用混合逻辑动态(MLD)框架简化了工业流程建模。 可以产生适用于工业过程的最佳控制问题。 例如,两个任意连接的MLD块被自动合并以获得一个复合MLD块。 通过重复使用该过程,可以从最简单的MLD构建块生成包含工业过程的完整描述的任何复杂的系统。 通过添加其唯一输出成为问题的成本函数的MLD块来生成最优控制问题。 在图形环境中,任何具体的工业过程可以通过从基本的MLD元素或原子MLD块的库中实例化块并通过适当地连接来再现。 在适当的库可用的情况下,除了构建所提到的图形互连的能力之外,该过程将不需要来自最终用户的任何专家知识。
    • 6. 发明申请
    • Process control system
    • 过程控制系统
    • US20050154476A1
    • 2005-07-14
    • US11019208
    • 2004-12-23
    • Eduardo GallesteyAlec Stothert
    • Eduardo GallesteyAlec Stothert
    • G05B13/04G05B13/02
    • G05B13/048G05B13/042
    • The inventive process control system makes use of Optimal control (OC) and model predictive control (MPC) techniques for selection of the Expert Systems (ES) targets U. The ES target U is selected in such a way that the performance criterion J is minimized. In other words, a mathematical model of extended system given by the process P and the ES is developed. This mathematical model has hybrid nature in the sense that both continuous dynamics (mostly process) and logical relationships (mostly ES) appear in it. Controlled variables of the mathematical model are the ES targets U and inputs are the measurements y and the performance criterion J. OC and/or MPC techniques are used to compute U. The optimizer of the OC/MPC selects values of the ES targets U only. This activity has lower sampling rates than selection of C, which makes the design of the OC/MPC controlled easier.
    • 本发明的过程控制系统利用最佳控制(OC)和模型预测控制(MPC)技术来选择专家系统(ES)目标U.ES目标U被选择为使得性能标准J最小化 。 换句话说,开发了由过程P和ES给出的扩展系统的数学模型。 这种数学模型具有混合性质,即连续动力学(主要是过程)和逻辑关系(主要是ES)出现在其中。 数学模型的受控变量是ES目标U,输入是测量y和性能标准J. OC和/或MPC技术用于计算U. OC / MPC的优化器仅选择ES目标的值U 。 该活动的采样率低于选择C,这使得OC / MPC的设计更容易控制。
    • 10. 发明授权
    • Optimizing plant control values of a power plant
    • 优化发电厂的工厂控制值
    • US07058552B2
    • 2006-06-06
    • US10021344
    • 2001-12-19
    • Alec StothertEduardo Gallestey AlvarezMarkus AhrensMarc AntoineSteve Morton
    • Alec StothertEduardo Gallestey AlvarezMarkus AhrensMarc AntoineSteve Morton
    • G06F17/10G06G7/48G05B13/02
    • G05B13/042
    • In a method and computer program product for optimizing power plant control values and a power plant optimizing system an optimization module (1) minimizes total plant operation costs while achieving predetermined required output values for produced power and process steam. This is done by, at a given time, determining future values of control values and simulating, in a simulation module (2), the behavior of the plant up to a given future time. Corresponding fuel costs and generated power are determined in the simulation, and incorporated in an objective function. The optimization module (1) minimizes the objective function by varying the control values. According to the invention, a rate of ageing of plant components is determined when simulating the future behavior of the plant, and the objective function to be minimized comprises said rate of ageing.
    • 在用于优化发电厂控制值的方法和计算机程序产品以及发电厂优化系统中,优化模块(1)最小化总设备运行成本,同时实现产生的功率和过程蒸汽的预定的所需输出值。 这通过在给定时间确定控制值的未来值并在模拟模块(2))中模拟工厂在给定未来时间的行为来完成。 相应的燃料成本和发电量在模拟中确定,并入目标函数。 优化模块(1)通过改变控制值来最小化目标函数。 根据本发明,在模拟植物的未来行为时确定植物组分的老化速率,并且要最小化的目标函数包括所述衰老速率。