Modeling and Control of pH Process for Weak Acid-Weak Base System | ||
| Engineering and Technology Journal | ||
| Article 1, Volume 30, Issue 1, January 2012, Pages 51-66 PDF (264.67 K) | ||
| DOI: 10.30684/etj.30.1.5 | ||
| Authors | ||
| Karima M. Butrus; Hayder A. Mohsin; Ali R. Mohammad Jawad | ||
| Abstract | ||
| This paper studies the model and control of pH neutralization process of waste water system using different control schemes. An experimental investigation was conducted for the dynamic behavior of neutralization process of waste water in a continuous stirred tank reactor (CSTR). A dynamic model for pH neutralization process in a continuous stirred tank reactor (CSTR) is described by a first order plus dead time (FOPDT). The pH value is calculated by solving the charge balance of the mixture. Good agreement is obtained between the simulated and experimental responses. However, a small differences between the responses due to the error in the measurements. The conventional feedback control was studies in this work and the controller parameters was tuned by Ziegler-Nichols reaction curve method to find the best values of proportional gain (Kc), integral time (t I) and derivative time (t D). Artificial Neural Network Model Predictive Control (ANN MPC) was used as another strategy to compare with above strategy. The ANN controller was compared with conventional controller and it was found that ANN controller provides better control for the set point changes with low settling time and lower overshoot. Whereas the conventional controller provides sluggish behavior in set point change. Also it was found that the ANN controller provides better response to regulated change than the conventional controllers where the PI and PID controllers provide sluggish disturbance responses because the approximate FOPTD model has relatively small time delay. As non-linear process the conventional feedback controller was unable to control this system adequately. | ||
| Keywords | ||
| Process Control; Neutralization Process; pH Control; Nonlinear Dynamic; ANN Control | ||
|
Statistics Article View: 351 PDF Download: 154 |
||