Abstract: The advantage of solving the complex nonlinear
problems by utilizing fuzzy logic methodologies is that the
experience or expert-s knowledge described as a fuzzy rule base can
be directly embedded into the systems for dealing with the problems.
The current limitation of appropriate and automated designing of
fuzzy controllers are focused in this paper. The structure discovery
and parameter adjustment of the Branched T-S fuzzy model is
addressed by a hybrid technique of type constrained sparse tree
algorithms. The simulation result for different system model is
evaluated and the identification error is observed to be minimum.