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Intermittent process 2D model prediction control method based on genetic algorithm optimization

A technology of model predictive control and genetic algorithm, applied in the direction of gene model, genetic rule, adaptive control, etc., can solve problems such as multi-stage and limitation of intermittent process

Active Publication Date: 2020-04-24
HAINAN NORMAL UNIVERSITY +1
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Problems solved by technology

However, current research results on uncertainties in multi-stage batch processes are greatly limited
In view of the above problems: the system is disturbed and the intermittent process is multi-stage, it is imperative to design a new model predictive control method to ensure that the intermittent process can still run smoothly under the influence of disturbance

Method used

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  • Intermittent process 2D model prediction control method based on genetic algorithm optimization
  • Intermittent process 2D model prediction control method based on genetic algorithm optimization
  • Intermittent process 2D model prediction control method based on genetic algorithm optimization

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Embodiment 1

[0232] In this embodiment, citing the conversion of the injection molding process from the injection section to the pressure holding section as an example, the injection section is defined as the first stage, and the pressure holding section is defined as the second stage.

[0233] After definition, in the injection section, the model of the injection velocity (IV) corresponding to the valve opening (VO) can be described as:

[0234]

[0235] And the nozzle pressure (NP) model corresponding to the injection velocity is:

[0236]

[0237] make u 1 (t,k)=VO(t,k),y 1 (t,k)=IV(t,k).

[0238] The response dynamics of the injection rate to the proportional valve has been described as a step mode, which translates into a state-space model as:

[0239]

[0240] Among them, δ(t,k) is a random variable between [0,1], and formula (36) is the state space model of the filling stage.

[0241] Similarly, in the pressure-holding section, the nozzle pressure model corresponding ...

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Abstract

The invention discloses an intermittent process 2D model prediction control method based on genetic algorithm optimization, which belongs to the industrial process control field. The method comprisesthe following steps of: 1, building a multistage intermittent process model with uncertainty, and building a 2D equivalent prediction control model, and 2, designing a model prediction tracking controller and a switching law. The optimal control of the intermittent process under the condition of worst interference is realized, the control performance influence caused by interference is solved, andgood tracking is realized. And meanwhile, the stability of the system is maintained and the performance of the system is ensured under unknown disturbance, and high-precision control is realized.

Description

technical field [0001] The invention belongs to the control field of industrial processes, and in particular relates to a 2D model predictive control method for intermittent processes based on genetic algorithm optimization. Background technique [0002] In modern industrial production, the batch process is widely used, especially in the food industry, pharmaceutical industry, chemical industry, etc., and the research on its control theory has also made great breakthroughs. However, it is still a challenge in the high-precision control of modern industrial processing, mainly due to its high-quality production level requirements and complex and changeable process conditions. Therefore, the system disturbance increases accordingly, and when the system is disturbed, the model will not match, making the system unable to run stably. Improving control performance in the presence of model mismatch remains an important issue. The iterative learning control strategy can effectively...

Claims

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Application Information

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IPC IPC(8): G05B13/04G06N3/12
CPCG05B13/045G05B13/048G06N3/126
Inventor 王立敏翟忆轩张日东罗卫平
Owner HAINAN NORMAL UNIVERSITY
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