Study On Fuzzy Control Strategies For Process Of Glyphosate Synthesis And The Integration Of Computer Control System

The synthesizing process of glyphosate is a typical batch production process. The production of glyphosate is mostly achieved by the organic synthesizing reaction. Its reaction mechanism is complex. The process must be controlled very well. Recently, many domestic companies that produce glyphosate by manual work are high labor intensity and low productivity. The Application of the distributed control system (DCS) can improve the precision of control so as to satisfy the rigorous request of the process. At the same time, it accomplishes the automation of production process, and improves product quality, reduces consumption, increases labor productivity.The synthesizing process of glyphosate is studied in the lecture. Each phase characteristic of the process is analyzed thoroughly. Proper control schemes are offered so as to accord with actual production condition, control request and production scale, mixing materials and weighing scheme, order control scheme and temperature control scheme included. By the advanced DCS control system, we make the production of glyphosate be a safety, green, clean way.Time-delay that frequently occurs in the temperature control in the production of glyphosate. Fuzzy Logic controller (FLC) has the advantages of free from the plant model, strong robustness and good stability against disturbances. So, a two-level expert fuzzy control scheme was developed to handle processes with large time delay. In the lower level, human simulated intelligent fuzzy controller, which combines such advantages as model-free, robustness of fuzzy logic controller and good ability to overcome delay of human-simulated intelligent controller, was employed, while in the supervisory control level, expert experience is was taken to tune both the quantitative factors and scale factor in an on-line manner. Simulation examples are included to illustrate that the proposed scheme is superior to Smith predictor and is effective in controlling of time-varying processes with large time delay.