Photobioreactor Control System Based On An Intelligent Decoupling Method

With the development of economy,the consumption of energy is far greater than the production of energy,and the unreasonable emission of fossil fuel has caused a series of environmental problems.Microalgae,with short growth cycle,low cost and oil content of 30%?50%of dry weight,is generally considered as the best raw materials for clean energy production.Photobioreactor is the main equipment for large-scale cultivation of microalgae.Temperature,p H and CO₂ are the key factors for algae growth.The control system of photobioreactor is a multi-input and multi-output control system.Most of the scholars have studied the temperature control in the reactor.There are few studies on other environmental factors,such as p H and CO₂,which affect the growth of algae cells and almost no consideration is given to the mutual influence of environmental factors.In fact,when a single factor is adjusted in the microalgae automatic culture device,other factors will be affected.For example,the increase of temperature will accelerate photosynthesis and affect CO₂ and p H,and if CO₂in algal solution reacts with water to form carbonic acid,the p H value will be reduced.Therefore,it is necessary to improve the control performance of photobioreactor to improve the efficiency and yield of microalgae culture.The research object of this paper is photobioreactor control system,the main research contents are as follows:Firstly,based on the research of photobioreactor control system,the phenomenon of strong coupling of temperature,p H value and CO₂ in the control system of photobioreactor is taken as the breakthrough point,and the key factors affecting the growth of Haematococcus pluvialis are considered to design a small-scale photobioreactor control system.After describing each subsystem in detail,the reliability of the designed system is tested by collecting the environmental factor data in real objects,which lays the foundation for the later data collection and model establishment.Secondly,because of the characteristics of large time delay,nonlinearity and strong coupling of photobioreactor control system,it is difficult to establish the model by mechanism method.Therefore,the experimental scheme is constantly improved,the experiments are repeated many times,and a large number of effective data are obtained.The mathematical models of temperature control loop,p H control loop and CO₂ control loop of photobioreactor are established by using step response curve method.The later system simulation lays the foundation.Thirdly,based on the classical control strategy PID algorithm and neural network algorithm with strong adaptive ability,a neural network PID Decoupling Control Algorithm for photobioreactor is proposed.The topology of neural network is 6×9×3 structure.The key point is to integrate P,I and D control into the three hidden layers of neural network and increase feedback as input.Through the error between input and output,the connection weights between neurons are updated,and finally the decoupling of temperature,p H value and CO₂ is realized.After the structure of neural network PID Decoupling Controller is designed,the weight iteration algorithm is mainly deduced.Finally,after analyzing the coupling of temperature control loop,p H control loop and CO₂control loop,MATLAB software is used to simulate the decoupling control of the system using traditional PID method and neural network PID strategy.Through the comparative analysis of simulation curves,the conclusion is drawn.For the same controlled object,the neural network PID controller designed in this paper can reduce the coupling phenomenon in photobioreactor,which provides a certain reference for large-scale cultivation of microalgae.