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Industrial process dynamic optimization system and method based on nonlinear conjugate gradient method

A conjugate gradient method, an industrial process technology, applied in the direction of comprehensive factory control, comprehensive factory control, electrical program control, etc., can solve difficult problems such as accuracy and high efficiency requirements

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

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Problems solved by technology

[0005] In order to overcome the deficiency that the existing industrial process dynamic optimization system and method are difficult to meet the accuracy and high efficiency requirements of online dynamic optimization solution at the same time, the present invention provides a non-linear based System and method for dynamic optimization of industrial process by conjugate gradient method

Method used

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  • Industrial process dynamic optimization system and method based on nonlinear conjugate gradient method
  • Industrial process dynamic optimization system and method based on nonlinear conjugate gradient method
  • Industrial process dynamic optimization system and method based on nonlinear conjugate gradient method

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Embodiment 1

[0113] Reference figure 1 , figure 2 , An industrial process dynamic optimization system based on nonlinear conjugate gradient method, including field intelligent instrument 2, DCS system and host computer 6 connected with industrial process object 1. Said DCS system consists of data interface 3 and operating station 4. The database 5 is composed; the field intelligent instrument 2 is connected to the communication network, the 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 operating station 4, the database 5 and the host computer 6. , The upper computer includes:

[0114] The constraint processing module 8 is used to process the boundary constraints of the control variables in the optimization process, using the following conversion equation:

[0115] u(t)=0.5(u max -u min )×{sin[w(t)]+1}+u min (1)

[0116] Will have boundary constraints u min ≤u(t)≤u max The control var...

Embodiment 2

[0163] Reference figure 1 with figure 2 , An industrial process dynamic optimization based on the nonlinear conjugate gradient method, the dynamic optimization method is implemented according to the following steps:

[0164] 1) Specify the state variables and control variables for dynamic optimization in the DCS system, and set the upper and lower boundaries of the control variables according to the conditions of the actual production environment and operating restrictions. max , U min And DCS sampling period, and the historical data of the corresponding variables in the DCS database 5 to control the upper and lower boundary values ​​u max , U min Sent to the host computer 6.

[0165] 2) In the constraint processing module 8 of the host computer, through trigonometric function substitution, the unconstrained conversion of the boundary-constrained control variable u(t) is performed, and it is replaced with the function expression of the intermediate variable w(t), namely :

[016...

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Abstract

The invention provides an industrial process dynamic optimization system based on a nonlinear conjugate gradient method, which comprises an in-site intelligent meter, a DCS system and a host machine, wherein the in-site intelligent meter is connected with an industrial process object, the host machine comprises a restriction processing module, an initialization processing module, an ODE solving module, an iteration optimization module and a convergence judgment module, the restriction processing module is used for processing the control variable boundary restriction in the optimization process, the initialization processing module is used for setting initialization parameters, the OED solving module is used for solving ordinary differential equation groups of a dynamic optimization question, the iteration optimization module is used for searching a decision vector w which makes a target function J optimum, the convergence judgment module is used for judging whether the error absolute value of the target value obtained by the current convergence and the target value obtained by the former convergence is smaller than or equal to the set convergence precision omicron, and the current optimum vector w*, the current optimum target value J* and the current convergence time number k are stored if the error absolute value of the target value obtained by the current convergence and the target value obtained by the former convergence is smaller than or equal to the set convergence precision omicron. The invention also provides an industrial process dynamic optimization method based on the nonlinear conjugate gradient method. The invention can simultaneously meet the requirements of high efficiency and high precision of the on-line dynamic optimization solving.

Description

Technical field [0001] The invention relates to the field of optimal control, in particular to an industrial process dynamic optimization system and method based on a nonlinear conjugate gradient method. Background technique [0002] Industrial process dynamic optimization is the core of process simulation technology and an important link in process optimization design, operation and control. The use of dynamic optimization methods to solve the bottleneck problems in process optimization control and tap the potential to increase efficiency has attracted more and more attention from the academic and industrial circles at home and abroad. [0003] As the demand for online optimal control in industrial processes continues to increase, it is becoming more and more important to improve the performance of dynamic optimization algorithms and increase the computational efficiency and accuracy of their online applications. [0004] The difficulty of industrial process dynamic optimization li...

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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