Adaptive identification and control of nonlinear systems using generalized fuzzy neural network.
Date of Issue2003
School of Electrical and Electronic Engineering
This thesis proposes a superior adaptive fuzzy neural network identification and control scheme for MIMO nonlinear dynamic systems in general, with a view of dealing with high complexity, uncertainties and imprecision in this class of systems. In literature, fuzzy logic and neural networks have been greatly adopted in modeling and control.
DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation
Nanyang Technological University