| The object of this paper is a control system of soft water treatment in XuChang tobacco factory. In the process of designing on software and hardware for the system, a few practical problems have been found. To solve these problems, we discuss the application of PLC, the intelligent control of objects with large lag and press control, and want to develop some new conclusions in practice and theory.The core of the control system of soft water treatment is a programmable logic controller(PLC). Adopting PLC can not only adapt to the technical features of water treatment, but also represent the tide of contemporary industry. SIMENS S7-300 PLC is a kind of programmable logic controller with a small scale, which is powerful in function and fast so that it can meet the requirements of analogy control with real time. On the basis of a detail introduction for modules of S7-300, this paper analyzed control requirements of every technical process, listed input and output signals, including digital signals and analogy signals, required to complete all control tasks. As far as control software, the paper introduced problems that need to be noticed and solved in the creation of control software according to the circumference and features of S7-300's program. The structure of software and control flow was come up accordingly in order to be helpful to the understanding of works of the paper.The highlight of this paper is research of control methods for process of PH. Process of PH is of large lag, nonlinear and time-varying. It is hard to establish a precise mathematical model for a PH process. Thought of features of PH process in middle tank in system of soft water treatment, this paper designed a kind of fuzzy controller combined feed-forward and feedback based on control strategy simulating human intelligence. The most important feature of the controller is that it imitates the control ideas of human beings who have been manipulating an object with large lag. It mainly emphasized on the problem of large lag, but could be adapted to nonlinear and time-vary of PH process through a fuzzy controller with feedback of parameters. It adopted a BP neural network with a lag factor to identify the counter static model of process and decided parameters of feed-forward control through a model image, adopted a feedback controller that can adjust fuzzy logic according to the changes of object's parameters to improve dynamic control effect and adopted a control strategysimulating human intelligence to harmony works of system by switching among each control combination. According to the operation in stage of adjustment, this control method is feasible. But the training of neural network need too much time so that the amount of adjustment work is increased. Therefore, a effective method to simulate offline will be helpful to improve the effect of this controller and enlarge its scope of application.In a water-supply system with constant press, press of punch has features that it is complicated, difficult to set up a precise mathematical model and with pure lag. So it is proper to control press with non-model control method based on man's experience. As far as the system of water treatment, water-supply control system with constant press has its features that on one hand it is an affiliation for other control system such as water level and PH process so that it needn't a high precise control, on the other hand it can be affected by other control system so that the object controlled is more complicated and indefinite. For those features, this paper designed a kind of fuzzy controller controlled by a simple expert system. In fact, this controller is added some confined conditions to a usual fuzzy controller to work normally when all kind of work conditions has been changing and to ensure the press of punch won't change so suddenly that it can be dangerous to machines in system. Adopting fuzzy logic is to adapt to complication and non-definition of object and to simplify the designing of software and adjustment. This paper adop... |
PDF Full Text Request