Information Technology Journal1812-56381812-5646Asian Network for Scientific Information10.3923/itj.2008.430.439El-KouatlyR. SalmanG.A. 3200873In this study, the application of the Radial Basis Function
(RBF) with Multiple Input and Multiple Output (MIMO) Neural networks to
control two types of non linear model plants of unknown dynamics. For
the first step a model of a control was developed using the variable liquid-level
which can be use in a chemical plant, or power station, where the liquid-level
is change within fixed real time. In this control system Radial Basis
Function (RBF) neural networks was used to control the liquid-level of
the plant. The second step introduced the changes of the liquid-level
in real time, also Radial Basis Function with MIMO neural networks has
been used to control the level liquid. The study shows that the proposed
control system produces accurate results for the two types of models.
However, we notice that the training, using back propagation, for the
second model take a more considerable time than training the first model.]]>Ahmed, M.S.,2000Chen, F.C. and H.K. Khalil,1992Diao, Y. and K.M. Passion,2002Ge, S.S. and C. Wang,2002Kosko, B.,1997Loannou, P. and B. Fidan,2006Murray, R.M., K.J. Astrom, S.P. Boyd, R.W. Brockett and G. Stein,2003Narendra, K.S. and K. Parthasarathy,1990Nounou, H.N. and K.M. Passino,2004Passino, K.M. and S. Yurkovich,1998Raun, D.,1997Sales, K.R. and S.A. Billings,1990Sanner, R.M. and J.J.E. Stoline,1992Xiaohong, J. and T. Shen,2005Wang, H., G.P. Liu and M. Brown,1995Wu, J.K.,1994