Control of nonlinear uncertain systems using type-2 fuzzy neural network and adaptive filter
Ching‐Hung Lee, Yu‐Ching Lin · 2004
In this paper, a new control scheme using type-2 fuzzy neural network and adaptive filter is proposed for controlling nonlinear uncertain systems. The used of type-2 FNN model combines the type-2 fuzzy logic system developed by Mendel, and the neural network. Our previous results shown that the type-2 FNN has the ability of universal approximation, i.e., identification of nonlinear systems. Then, we adopt it to develop a control scheme for nonlinear uncertain systems. In order to have a better performance of transient response with step input, an adaptive filter has been used to develop a two-degree-of-freedom control scheme. The tuning parameter of filter and type-2 FNN changes according to the needs of learning algorithm. The effectiveness of the proposed controller is demonstrated by simulated results.