Abstract
A novel dynamical neuro-fuzzy network (DFNN) is provided in paper [5]. DFNN based on the forward neuro-fuzzy network ANFIS combines the advantages of fuzzy system, neural network and PID algorithm by adding a recurrent layer between the normalized layer and output layer of ANFIS. This paper simplified the structure of DFNN and a simplified dynamical fuzzy neural network (SDFNN) is proposed. SDFNN adopts only one recurrent neuron in recurrent layer by connected to the outputs of Fuzzy zero rules, so a kind of PID controller is realized by SDFNN. The simulation results show SDFNN has the quick response as ANFIS does but possess the higher performance accuracy than ANFIS.
| Original language | English |
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| Pages | 998-1001 |
| Number of pages | 4 |
| Publication status | Published - 2000 |
| Event | Proceedings of the 3th World Congress on Intelligent Control and Automation - Hefei, China Duration: 28 Jun 2000 → 2 Jul 2000 |
Conference
| Conference | Proceedings of the 3th World Congress on Intelligent Control and Automation |
|---|---|
| Country/Territory | China |
| City | Hefei |
| Period | 28/06/00 → 2/07/00 |
Keywords
- Dynamical Neuro-fuzzy network
- Learning algorithm
- Recurrent system