Based On Neural Networks In The Ph And The Process Of Identification And Controller Design,

pH neutralization process is a typical nonlinear process, and often contains long time-delay part, so the identification and control of such process is one of the difficult problems in control field, how to deal with the nonlinear problem and long time-delay part of the system is the key. The research on this problem is developed in the thesis using artificial neural network theory, especially Universal Learning Network (ULN) used in this field the first time, and the method of identification and control based on the ULN is presented.Universal learning network is a new type of artificial neural network. In the network, all the nodes are connected each other, and on each connection of the network, arbitrary time-delay can be set. Compared with traditional neural network, the structure of ULN is more compact; when ULN is adopted in the system with long time-delay, the network can embody the long time-delay properly, which establish the base for ULN to identity nonlinear dynamical system with long time-delay.The pH neutralization process is identified with universal learning network, and compared with other method like BP, RBF network, the simulation result shows that the effect of ULN is better than that of other methods, the generalizing ability is good, and the network can embodied the dynamical, nonlinear and long time-delay character very well.The identification with ULN establishes the base for effective control of pH neutralization process. The ULN model that got through identification is able to predict the output of the plant in the future time simply, so it can be used as the predictor and predicting model, then the infection of the long time-delay can be eliminated effectively, and the controller can get the proper information of the plant in time. In the paper, the following methods are used to control the system: PID method, model predictive control + PID method, neural network PID + ULN predictor method, single neuron controller + ULN predictor method. The result shows that, the effect of ULN in control system is obvious, and the control effect improves obviously. The rising time and stable time are decreased, and the overshot become smaller also. The ability of resisting disturbance of the system also improves much.Altogether, aiming at the pH neutralization process, the method based on the ULN is presented, and the validity of ULN in this field is validated.