Adaptive PID anaerobic fermentation temperature control system and method based on Elman neural network

A technology of temperature control system and temperature control method, which is applied in the direction of temperature control using electric methods, electric controllers, controllers with specific characteristics, etc., which can solve problems such as poor combustion control, low solar energy density, and large weather influence , to achieve the effects of ensuring stability and robustness, improving responsiveness, and strong time-varying

Pending Publication Date: 2022-03-08
国能生物发电集团有限公司
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  • Application Information

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Problems solved by technology

These technologies have some shortcomings. For example, the heating technology of electrothermal film combined with insulation layer needs to consume high-grade electric energy, which has high energy consumption and poor energy-saving performance; the combustion pool heating technology uses low-grade fuels such as sawdust and straw for heating, but the combustion control is relatively poor. The management and operation are relatively complicated; the energy density of solar energy is low, the day and night changes are large, and it is greatly affected by the weather, so it is difficult to ensure the temperature required by the anaerobic fermentation system

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  • Adaptive PID anaerobic fermentation temperature control system and method based on Elman neural network
  • Adaptive PID anaerobic fermentation temperature control system and method based on Elman neural network
  • Adaptive PID anaerobic fermentation temperature control system and method based on Elman neural network

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Example Embodiment

[0036] Example 1

[0037] ELMAN-based neural network adaptive PID anaerobic fermentation temperature control system, such as figure 1As shown, including flue gas waste heat exchangers, slag residual heat heat exchangers, lap-saver heat exchangers, heating circulating heat exchanger, temperature monitor, constant temperature water storage tank, and neural network -PID controller; said smoke The remaining heat heat exchange unit is connected to the constant temperature storage tank, and the smoke heat heating circulating water of the direct-fired power generation system is recovered to the constant temperature storage tank; the slag residual heat heat exchange is connected to the constant temperature storage tank and recovered direct-fire power generation. The slag heat heating circulating water is sent to a constant temperature storage tank; the lapse of the steam is connected to the constant temperature storage tank, recovering the lack of fire-fuel power generation system to the con

Example Embodiment

[0052] Example 2

[0053] ELMAN-based neural network adaptive PID anaerobic fermentation temperature control system, such as figure 1 As shown, including flue gas waste heat exchangers, slag residual heat heat exchangers, lap-saver heat exchangers, heating circulating heat exchanger, temperature monitor, constant temperature water storage tank, and neural network -PID controller; said smoke The remaining heat heat exchange unit is connected to the constant temperature storage tank, and the smoke heat heating circulating water of the direct-fired power generation system is recovered to the constant temperature storage tank; the slag residual heat heat exchange is connected to the constant temperature storage tank and recovered direct-fire power generation. The slag heat heating circulating water is sent to a constant temperature storage tank; the lapse of the steam is connected to the constant temperature storage tank, recovering the lack of fire-fuel power generation system to the co

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Abstract

The invention provides a self-adaptive PID anaerobic fermentation temperature control system and method based on an Elman neural network, and the system mainly comprises a flue gas waste heat exchanger, a deslagging waste heat exchanger, a dead steam waste heat exchanger, a heating circulation heat exchanger, a temperature monitor, a constant-temperature water storage tank, and a neural network-PID controller. The control method comprises the following steps: presetting an anaerobic fermentation target temperature, obtaining a current time temperature, adaptively adjusting parameters of a PID controller through an Elman neural network according to a difference value between the current temperature and the target temperature, and then controlling output of a heat exchanger by using a PID algorithm, thereby realizing adaptive adjustment of the anaerobic fermentation temperature. The temperature control system utilizes waste heat of a power plant to maintain the anaerobic fermentation temperature, and has remarkable energy-saving benefits; according to the control method, a neural network self-adaptive PID algorithm is adopted, interference of large fluctuation and time-varying characteristics of a direct-fired power generation and anaerobic fermentation system on the system is overcome, temperature control precision and accuracy are guaranteed, and good robustness is achieved.

Description

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Claims

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Application Information

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Owner 国能生物发电集团有限公司
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