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Thermal process model parameter identification method adopting improved ant colony algorithm

A process model and parameter identification technology, applied in the field of thermal process model parameter identification, can solve problems such as poor versatility, dependence on calculation accuracy, and difficulty in application

Inactive Publication Date: 2016-03-09
SOUTHEAST UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Due to the limitations of factors such as field operating conditions and test time, the latter three methods are difficult to be applied in practice
When the step response curve is relatively regular, the approximate method, semi-logarithmic method, tangent method and two-point method can be used to effectively derive the transfer function, but the calculation accuracy of these methods depends on the surveying and mapping instrument, so the versatility is relatively poor; when When the step response curve has an irregular shape, the area method can be used, but the area method has the disadvantages of being easy to fall into a local minimum, so it is only suitable for simple objects with white balance capabilities

Method used

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  • Thermal process model parameter identification method adopting improved ant colony algorithm
  • Thermal process model parameter identification method adopting improved ant colony algorithm
  • Thermal process model parameter identification method adopting improved ant colony algorithm

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Experimental program
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Effect test

Embodiment 1

[0071] The thermal process model was identified on MATLAB, and compared with the parameter identification results using the basic ant colony algorithm. The structural thermal process model is as follows:

[0072] G ( s ) = 12.3 ( 1 + 54.3 s ) 5 e - 123 s - - - ( 7 )

[0073] Select m=30, α=1.1, ρ=0.1, the number of iterations is 50, use e(n) to record the minimum value of the identification error for each iteration, and the algorithm will stop executing when the number of iterations reaches 50 or e(n) is equal to 0. The selection range of model parameters is: K ∈ (-29.9, 29.9), ...

Embodiment 2

[0081] Figure 5 When the 300MW circulating fluidized bed boiler operates between 200MW-250MW load, keep other input volumes unchanged, and increase the primary air volume by 16km 3 / h, the effect curve on bed pressure. It can be seen that when the primary air volume increases, the bed pressure drops rapidly, and the entire drop process takes about 60s.

[0082] Set parameters m=30, α=1.1, ρ=0.1, and the number of iterations is 50. The selection range of model parameters is: K ∈ (-0.499, 0), T ∈ (0, 49.9), n ∈ (1, 5). The transfer function model identified by the basic ant colony algorithm is:

[0083] G ( s ) = - 0.096 ( 1 + 19 s ) 3 - - - ( 10 ) ...

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Abstract

The invention discloses a thermal process model parameter identification method adopting an improved ant colony algorithm. The thermal process model parameter identification method comprises the steps of determining a system identification structure and parameters to be identified, determining algorithm path and initial pheromone distribution and completing the search through loop iteration. The thermal process model parameter identification method makes some corresponding improvements to a thermal process on the basis of the basic ant colony algorithm, and converts an identification problem into an optimization problem in a parameter space, so that the algorithm is more accurate and efficient. On the basis of known input and output data, the thermal process model parameter identification method adopts the improved ant colony algorithm on MATLAB software for carrying out efficient and parallel search on the entire parameter space, can identify model parameters quickly, and achieves the precise modeling purpose.

Description

technical field [0001] The invention relates to the field of thermal control, in particular to a thermal process model parameter identification method using an improved ant colony algorithm. Background technique [0002] In recent years, new energy power generation technology has developed rapidly, but thermal power will still be the main form of installed power in my country for a period of time in the future, playing a pillar role in my country's economic development. In-depth research on the characteristics of thermal power units, especially the development of energy-saving and emission-reduction technologies, plays an important role in the development of a resource-saving and environment-friendly national economy. Combined with the development trend of high parameters, large capacity and high automation of thermal power units in my country, the characteristics of multivariable coupling, complex structure, uncertainty and nonlinearity of the thermal system of thermal powe...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06N3/00
CPCG06Q10/04G06N3/006
Inventor 张雨飞章程明
Owner SOUTHEAST UNIV
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