Realization of Fuzzy-smith Control on PLC and Its Application

Delay system as an important part of the complex control system , widely exist in modern industrial processes . At the same time , it is also an important field of application control theory , and therefore have important implications for the study of delay systems . In this paper, Smith control method for delay systems , and tank level control . By experimental modeling and mechanism modeling method to establish the electric control valve and tank level sensor , a generalized mathematical model of the object . Delay characteristics of the controlled object , in order to improve the robustness of the Smith predictor , using fuzzy the Smith structure of the controller . Fuzzy control to eliminate the steady-state error caused fuzzy Smith predictor controller design with integral action . Using Matlab / Simulink simulation of the control algorithm , simulation results show good robustness with integral fuzzy Smith control , the overshoot response time has better control quality , and can achieve steady-state static error . Smith Control requires accurate mathematical model of controlled object , and make use of the advantages of adaptive control , respectively, based on the local parameter optimization theory and Lyapunov stability theory , adaptive Smith controller design . The simulation results show that the adaptive Smith controller have good robust performance , and dynamic performance and anti-jamming . According to the above theory and simulation studies , with integral fuzzy Smith control is applied Tianhuang ordinance THJ-1 process control experimental apparatus tank level control of the system controller for Siemens S7 -300 PLC . The offline calculated the fuzzy lookup tables , discretization Smith predictor algorithm using controller programming software STEP7 write the program to implement the control algorithm in the Siemens S7-300 PLC . WinCC configuration software, design experiments monitoring interface and real-time monitoring of the experimental process . The results showed that the Fuzzy Smith control algorithm used in this article , does not require a precise mathematical model of controlled object , can be effectively overcome the time delay , better quality control , strong robustness .