Research On Cold Storage Temperature Of Fishing Boat Based On BP Neural Network PID Control

With the continuous development of fishery and fishing industry in coastal areas and the support of national policies,the number of newly built and renovated frozen fishing vessel in China has increased rapidly,and the yield of fish has greatly increased.Among them,freezing preservation treatment is an important link of storage and transportation,and the fishing vessel cold storage refrigeration system will also become its key.This thesis mainly studies the cooling temperature control of fishing vessel cold storage as the object.Through the analysis of the cooling control principle of fishing vessel cold storage and the characteristics of the actual environment of fishing vessel cold storage,on the premise of ensuring that the simulation model can accurately reflect the real environment,using idealized simulation,the cold storage temperature transfer function model is established.The control temperature of fishing boat cold storage refrigeration is mainly controlled by traditional PID(Proportional-Integral-Derivative),which has the problems of delay response,nonlinear,weak stability and poor robustness.In this thesis,the more popular BP neural network intelligent algorithm and the combination of traditional PID temperature control,the use of intelligent neural network intelligent control means,the output of the three parameters(proportional coefficient,integral coefficient,differential coefficient)constantly transform and set,until the most similar effect with the desired control results.By using the special simulation function of MATLAB software,the cold storage temperature transfer function is substituted into the controller,and the output results of the traditional PID controller and BP(Back Propagation)neural network PID controller are simulated and compared.The result shows that the response time of the latter is faster,the stability is better and the robustness is stronger than the former.The simulation study also finds the proportional combination of the optimal output parameters of this control method:proportional coefficient =0.4977,integral coefficient =0.0013,differential coefficient=0.3950.This thesis also designed man-machine control interface into BP neural network PID temperature control,remote control of fishing boat refrigeration equipment using mobile phone interface,improve the level of automation.Based on this combination design of BP neural network PID temperature controller for cold storage temperature control can not only ensure the stability of temperature and can control energy consumption in the lowest range,but also can greatly improve efficiency and save costs,provide convenience.