A TSK-type fuzzy neural network (TFNN) systems for dynamic systems identification
Ching‐Hung Lee, Wei-Yu Lai, Yu‐Ching Lin · 2004
In this paper, a TSK-type fuzzy neural network system (TFNN) for identifying unknown dynamic systems is proposed. The TFNN system can learn its knowledge base from input-output training data. Thus, the unknown system is represented as several if-then rules with TSK-type consequent parts. The TFNN system can be randomly initialized and then trained by the back-propagation algorithm. Several examples are presented to illustrate the effectiveness of our approach.