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High-efficiency system and method for dynamic optimization of industrial process

An industrial process, dynamic optimization technology, applied in the direction of comprehensive factory control, comprehensive factory control, electrical program control, etc., can solve problems such as poor applicability of optimal solutions

Inactive Publication Date: 2010-06-30
ZHEJIANG UNIV
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  • Application Information

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Problems solved by technology

[0004] In order to overcome the shortcomings of the existing industrial process dynamic optimization system and method that it is difficult to find the optimal solution accurately and quickly, and the applicability is poor, the present invention provides a method that can accurately find the optimal solution of complex nonlinear dynamic optimization problems and converge Efficient industrial process dynamic optimization system and method with high speed and wide applicability

Method used

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  • High-efficiency system and method for dynamic optimization of industrial process
  • High-efficiency system and method for dynamic optimization of industrial process
  • High-efficiency system and method for dynamic optimization of industrial process

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Experimental program
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Embodiment 1

[0090] refer to figure 1 , figure 2, a highly efficient industrial process dynamic optimization system, including on-site intelligent instrument 2 connected with industrial process object 1, a DCS system and a host computer 6, the DCS system is composed of a data interface 3, an operation station 4, and a database 5; The smart meter 2 is connected to the data communication network, the data communication network is connected to the data interface 3, the data interface 3 is connected to the field bus, and the field bus is connected to the operation station 4, the database 5 and the upper computer 6, and the described The upper computer 6 includes:

[0091] The initialization module 8 is used for the setting of initial parameters, discretization and initial assignment of state vector x(t) and control vector u(t), and the specific steps are as follows:

[0092] 2.1) The time domain t∈[t 0 , tf] is divided into NE segments: [t 0 , t 1 ], [t 1 , t 2 ],...,[t NE-1 , t NE ]...

Embodiment 2

[0129] refer to figure 1 and figure 2 , a highly efficient dynamic optimization method for industrial processes, the dynamic optimization method is implemented according to the following steps:

[0130] 1) Specify the dynamically optimized state variables and control variables in the DCS system, and set the upper and lower boundaries u of the control vector according to the conditions of the actual production environment and operating restrictions ub , u lb and the sampling period of the DCS, and the historical data of the corresponding variables in the DCS database 5, the upper and lower boundary values ​​of the control variables u ub , u lb Send to the host computer;

[0131] 2) In the initialization module 8, the initial parameters are set, and the data input by the DCS system is initialized, and it is completed according to the following steps:

[0132] 2.1) The time domain t∈[t 0 , tf] is divided into NE segments: [t 0 , t 1 ], [t 1 , t 2 ],...,[t NE-1 , t NE...

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Abstract

The invention relates to a high-efficiency system for the dynamic optimization of an industrial process. The system comprises a field intelligent instrument, a DCS system and an upper computer, wherein the field intelligent instrument is connected with an industrial process target. The upper computer comprises an initialization module, a variant configuration module, a constraint enforcement module, a model transformation module and an NLP solution module, wherein initialization module is used to set initial parameters; the variant configuration module is used to conduct Lagrange interpolation conversion and to take the root of Legendre polynomials as a configuration point; the constraint enforcement module is used to enforce constrains on control vector u (t) and time division length hi; the model transformation module is used to discretize a dynamic optimization model, to increase state vector continuity conditions and the constraint conditions of the constraint enforcement module, and to convert an infinite dimensional dynamic optimization problem into a finite dimensional nonlinear programming problem; and the NLP solution module is used to solve the finite dimensional nonlinear programming problem obtained by the model transformation module. The invention additionally provides a method for the dynamic optimization of the industrial process. The invention hast the advantages that the optimum solution to the complex nonlinear dynamic optimization problem can be accurately found, the convergence rate is very high and the applicability is wide.

Description

technical field [0001] The invention relates to the field of optimal control, in particular to an efficient industrial process dynamic optimization system and method. Background technique [0002] In recent years, with the continuous improvement of modern industrial process performance requirements and the development of powerful commercial software such as Aspen and gPROMS, dynamic simulation and dynamic optimization of process industry have been more and more widely developed and applied. Dynamic optimization research has become a focus and hotspot in industrial process optimization design, operation and control research. [0003] The optimization model of industrial process dynamic system often contains a set of complex large-scale nonlinear differential equations, and also includes nonlinear equality or inequality path constraints and point constraints. Therefore, the difficulty of dynamic optimization lies in the need to seek the optimal value of the target functional ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B19/418
CPCY02P90/02
Inventor 刘兴高陈珑
Owner ZHEJIANG UNIV
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