Control system and control method for feeding prediction control in process of fuel ethanol preparation through straw fermentation based on fuzzy neural network

Abstract

A control method and a control system for feeding prediction control in the process of fuel ethanol preparation through straw fermentation based on a fuzzy neural network are disclosed. The control method comprises the following steps: firstly, training a fuzzy neural network and building a nonlinear prediction model of the process of fuel ethanol preparation through straw fermentation according to historical batch data; secondly, predicting the future output state of the process of fuel ethanol preparation through straw fermentation according to the prediction model and by use of the input / output information of historical and future batch data, and performing feedback correction on model output error to get closed-loop output; and finally, comparing the closed-loop output with a reference input track, using quadratic performance indexes to carry out rolling optimization, and calculating out the feeding control quantity which needs to be applied to the system currently. The control system comprises field intelligent detection instruments, peristaltic pumps and an intelligent controller, wherein the field intelligent detection instruments and the peristaltic pumps are directly connected with a fermentation tank, the intelligent controller adopts an embedded ARM microprocessor technology, and a feeding prediction control algorithm is embedded into the intelligent controller. The control system and the control method of the invention can adapt to the dynamic characteristic, strong nonlinearity and strong coupling between loops in the process of fuel ethanol preparation through straw fermentation. A good control effect can be achieved.

Description

technical field [0001] The invention belongs to the interdisciplinary field of biotechnology and information science, and mainly relates to a method and a system construction method for automatically controlling the amount of supplementary materials—glucose, ammonia water, and ammonium sulfate—in the process of straw fermentation fuel ethanol. Background technique [0002] With the increasingly serious environmental pollution and the intensifying energy crisis, biomass energy has been praised by countries all over the world as a sunrise industry with huge economic potential due to its huge resources, convenient use, cleanliness and pollution-free characteristics. Biomass energy mainly includes fuel ethanol, biodiesel, biogas, and biohydrogen production. Among them, fuel ethanol is the largest biomass energy produced and used in the world, and it is the only one extracted from biomass that can be directly used in vehicles. The liquid energy carrier of fuel, especially the p...

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Problems solved by technology

[0006] In order to overcome the deficiencies of the existing feeding control schemes that cannot adapt to the dynamic characteristics of the straw fermentation fuel ethanol process, strong nonlinearity, coupling between loops, and failure to obtain good control effects, the present invention provides a solution that can solve the problem of straw Fuzzy neural network-based feed predictive control method and system for straw fermentation fuel ethanol process based on the dynamic characteristics, strong nonlinearity, and coupling problems between loops in the fermentation fuel ethanol process, and obtained good control effect

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