The Design Of Based On Fuzzy Control In The Automatic Control System Of Aeration For CASS Process

Sewage biochemical treatment process, CASS process has many uniqueadvantages, and a wide range of applications. However, from the point of view of theautomatic control method， CASS Process Act biochemical reaction mechanism is verycomplex: a nonlinear, multi-variable influent water quality, seasonal changes intemperature and other factors affect the time variability, complexity and randomness,for the above-mentioned problems, the existing manual control and the application oftraditional control theory can not be the ideal control effect. So they need a better playto the advantage of CASS process control, but also can guarantee the system stabilitycontinue the run.I then combined with the existing research results, the use of fuzzy control theory,combined with the actual situation and the issues involved in our factory to design acontroller based on the fuzzy theory, and do the following work:1, A brief introduction to the automation of the current situation of the domesticand international sewage treatment;Sewage activated sludge treatment process was introduced;3, The actual structure of the plant, the CASS process, principles, processes areintroduced;4, Taking into account the complexity of the control system of the sewagetreatment plant, I only studied in which part of the problem, specific solutions andresults are given for the problem of the actual situation of the factory: changesaccording to the characteristics of CASS reaction cell process variations and thedissolved oxygen the characteristics of fuzzy controller design principles, methods;process data based on the simulation results given fuzzy control strategy applications.Actual observations and studies have shown that: sewage biochemical treatmentprocess (such as SBR process, oxidation ditch process, A2-O, CASS process) theconcentration of dissolved oxygen in the water control system is a typical large lag,large inertia, uncertainty system. For such a system, the control problems facing mustbe using a special control strategy to resolve. Fuzzy control from the experience of operating personnel and experts to make decisions without the need for a mathematicalmodel of a nonlinear control. And weaken the impact of the interference parameterchanges on the system control effect.