Journal of Applied Sciences1812-56541812-5662Asian Network for Scientific Information10.3923/jas.2014.1576.1581SowmyaP.BalasubramanianG.RakeshkumarS.RamkumarK.1220141414This study addresses the design of Genetic Algorithm (GA) based fuzzy controller for the non linear process. The process taken for this study is conical tank since most of the chemical industries use the same. The model of the process is identified by introducing a step change in inlet flow rate to the tank and recording the change in level with respect to time. The recorded data is plotted against time which is process reaction curve. From the process reaction curve the model parameter of the process is identified. For the identified model different controllers such as Internal Model Controller (IMC), fuzzy and GA based fuzzy controllers are designed and implemented in MATLAB environment. It was observed that GA based fuzzy controller outperformed the other controllers in terms of performance indices such as Integral Square Error (ISE), Integral Time Absolute Error (ITAE) and Integral Absolute Error (IAE) and Time domain specifications.]]>Astrom, K.J. and T. Hagglund,2004Zupancic, B., M. Klopcic and R. Karba,1993Chien, I.L. and P.S. Fruehauf,1990Fileti, A.M.F., A.J.B. Antunes, F.V. Silva, V. Silveira Jr. and J.A.F.R. Pereira,2007Herrero, J.M., X. Blasco, M. Martinez and J.V. Salcedo,2002Kumar, M.P. and S. Vijayachitra,2009Mamdani, E.H.,1974Jain, R., N. Sivakumaran and T.K. Radhakrishnan,2011Sowmya, P., N. Srivignesh, N. Sivakumaran and G. Balasubramanian,2012Sundaresan, K.R. and R.R. Krishnaswamy,1978Wang, H.O., K. Tanaka and M.F. Griffin,1996Zadeh, L.A.,1965Ziegler, J.G., N.B. Nichols and N.Y. Rochester,1942