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

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...

Images