The Research Of Industrial Temperature Controller Based On Fuzzy-control

Fuzzy control belongs to the field of intelligent control, based on linguistic rules. The starting point of the traditional PID control is on the basis of the accurate mathematical model of object, but it is impossible or too complex to obtain. Fuzzy control is based on the fuzzy math, which doesn't require accurate mathematical model. Fuzzy control only needs to build up certain control rules, then has strong adaptability faced with different object, so fuzzy control theory gets more and more extensive application. Combined with advanced hardware technique, this paper discusses the fuzzy control applyed to the temperature control system and fuzzy language control strategy changed into valid automatic control strategy. Making use of the strong manipulative and calculative function of microcontroller, this paper designs a fuzzy controller with AT89S51 as the core.In addition, this paper does certain study on the area network of the fuzzy control and uses the popular CAN bus technology to adapt to the demand of high-speed communication ability in the particular situation. CAN bus is generally recognized as one of the developmental Fieldbus. CAN bus interfere of fuzzy controller is designed with chip SJA1000 and still keeps the RS232/RS485 communication mode which was accustomed before. Then this fuzzy controller can be adapted to different demands .It can be used not only independently, but also be applied to centralized or distributed control. In a word, the designed control network has strong agility.The verification of the result is to take full advantage of Fuzzy-logic toolbox and SIMULINK in MATLAB. The fuzzy interfere system is established in the Fuzzy-logic toolbox as a parameter to transfer to fuzzy control simulate model. The simulation about fuzzy control is compared with PID control, and in the condition of Robust (It can be explained that control system will still keep the constant function about the quality index when its characteristic or parameter changing). At last, the factual running situation is simulated by the fuzzy control. This simulation result shows that it is possible to achieve the anticipative control performance by applying the fuzzy control method to the temperature system. It is simple, feasible and practical.