摘要
Tubular flow reactors are mainly used in chemical industry and waste water discharged units. Control of output variables is very difficult because of the existence of high dead-time in these types of reactors. In the present work, sodium hydroxide and acetic acid solutions were sent to the tubular flow reactor. The aim was to control p H at 7 in the nonlinear region. The p H control of a tubular flow reactor with high time delay and a highly nonlinear behavior in p H neutralization reaction was investigated experimentally in the face of the various load and set point changes. Firstly, efficiency of conventional Proportional-Integral-Derivative(PID) algorithm in the experiments was tested. Then self-tuning PID(STPID) control system was applied by using the ARMAX model. The model parameters were calculated from input–output data by using PRBS signal as disturbance and Bierman algorithm. Lastly, the experimental fuzzy control of p H based on fuzzy model was achieved to compare the success of fuzzy approach with the performance of other control cases studied.
Tubular flow reactors are mainly used in chemical industry and waste water discharged units. Control of output variables is very difficult because of the existence of high dead-time in these types of reactors. In the present work, sodium hydroxide and acetic acid solutions were sent to the tubular flow reactor. The aim was to control p H at 7 in the nonlinear region. The p H control of a tubular flow reactor with high time delay and a highly nonlinear behavior in p H neutralization reaction was investigated experimentally in the face of the various load and set point changes. Firstly, efficiency of conventional Proportional-Integral-Derivative（PID） algorithm in the experiments was tested. Then self-tuning PID（STPID） control system was applied by using the ARMAX model. The model parameters were calculated from input–output data by using PRBS signal as disturbance and Bierman algorithm. Lastly, the experimental fuzzy control of p H based on fuzzy model was achieved to compare the success of fuzzy approach with the performance of other control cases studied.
