References

Gulaian, M. and J. Lane, 1990. Titration curve estimation for adaptive pH control. Proceedings of the American Control Conference, May 23-25, San Diego, CA., pp: 1414-1419.

Guner, E., 2003. Adaptive neuro fuzzy inference system applications in chemical processes. Master of Science, Middle East Technical University, Ankara.

Gupta, R.A., R. Kumar and R.S. Surjuse, 2009. ANFIS based intelligent control of vector controlled induction motor drive. Proceedings of the 2nd International Conference on Emerging Trends in Engineering and Technology, Dec. 16-18, Nagpur, India, pp: 674-680.

Henson, M.A. and D.E. Seborg, 1994. Adaptive nonlinear control of a pH neutralization process. IEEE Trans. Control Syst. Technol., 2: 169-182.
CrossRef  |  Direct Link  |  

Luyben, W.L., 1989. Process Modeling, Simulation and Control for Chemical Engineers. McGraw-Hill, Ohio.

Magada, L.O., 2008. Multivariate statistical process control and case-based reasoning for situation assessment of sequencing batch reactor. Ph.D. Thesis, Universitat de Girona Catalonia.

Ogunnaik, B.A. and W.H. Ray, 1994. Process Dynamics, Modeling and Control. Oxford University Press, UK.

Parekh, M., M. Desai, H. Li and R.R. Rhinehart, 1994. In-line control of nonlinear pH neutralization based on fuzzy logic. IEEE Trans. Components, Packag. Manuf. Technol. A, 17: 192-201.
CrossRef  |  

Pishvaie, M.R. and M. Shahrokhi, 2006. Control of pH processes using fuzzy modeling of titration curve. Fuzzy Sets Syst., 157: 2983-3006.
CrossRef  |  

Qin, S.J. and G. Borders, 1994. A multi-region fuzzy logic controller for nonlinear process control. Proc. IEEE Trans. Fuzzy Syst., 2: 74-81.
CrossRef  |  

Shinskey, F.G., 1974. Adaptive pH controller monitor nonlinear process. Control Eng., 21: 57-60.

Vojtesek, J. and P. Dostal, 2005. From steady-state and dynamic analysis to adaptive control of the CSTR reactor. Proceedings of the 19th European Conference on Modeling and Simulation, June 1-4, Riga, Latvia, pp: 591-598.