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

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

Inactive Publication Date: 2011-08-31
ZHEJIANG UNIV
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  • Claims
  • 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

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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

Examples

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Embodiment 1

[0113] refer to figure 1 , figure 2 , an industrial process dynamic optimization system based on the nonlinear conjugate gradient method, including a field smart instrument 2 connected to an industrial process object 1, a DCS system and a host computer 6, and the DCS system consists of a data interface 3 and an operating station 4 , database 5; the field smart 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 operation station 4, the database 5 and the upper computer 6 , the host computer includes:

[0114] The constraint processing module 8 is used to process the control variable boundary constraints in the optimization process, and adopts the following conversion equation:

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

[0116] will be bounded by u min ≤u(t)≤u max The control variable u(t) is tr...

Embodiment 2

[0163] refer to figure 1 and figure 2 , a dynamic optimization of an industrial process based on a nonlinear conjugate gradient method, the dynamic optimization method is implemented according to the following steps:

[0164] 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 variables according to the conditions of the actual production environment and operating restrictions max , u min 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 max , u min Send it to the host computer 6.

[0165] 2) In the constraint processing module 8 of the upper computer, the control variable u(t) constrained by the boundary is converted unconstrainedly through trigonometric function substitution, and replaced by the functional expression of the intermediate variable w...

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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 currentoptimum 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 thetarget 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] Dynamic optimization of industrial process is the core of process simulation technology and an important part of process optimization design, operation and control. The use of dynamic optimization methods to solve the bottleneck problem in process optimization control and to tap the potential and increase efficiency has been paid more and more attention by domestic and foreign academic and industrial circles. [0003] With the increasing demand for online optimal control of industrial processes, it is becoming more and more important to improve the performance of dynamic optimization algorithms and improve the computational efficiency and accuracy of their online applications. [0004] The difficulty in the dynamic optimization of industrial pr...

Claims

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Application Information

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