Inversion of fuzzy neural networks for the reduction of noise in the control loop
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
Authors
A robust throttle valve control has always been a attractive problem since throttle by wire systems were established in the mid-nineties. Often in control strategy, a feedforward controller is adopted in which an inverse model is used. Mathematical inversions of models imply a high order of differentiation of the state variables and consequently noise effects. In general, neural networks are a very effective and popular tool mostly used for modeling. The inversion of a neural network produces real possibilities to involve the networks in the control problem schemes. This paper presents a control strategy based upon an inversion of a feed forward trained local linear model tree. The local linear model tree is realized through a fuzzy neural network. Simulated results from real data measurements are presented in which two control loops are explicitly compared
| Original language | English |
|---|---|
| Title of host publication | Intelligent Manufacturing Systems |
| Editors | Carlos Eduardo Pereira, Oleg Zaikin, Zbigniew A. Banaszak |
| Number of pages | 6 |
| Volume | 9 |
| Publisher | International Federation of Automatic Control |
| Publication date | 2008 |
| Pages | 157-162 |
| ISBN (print) | 978-3-902661-40-1 |
| DOIs | |
| Publication status | Published - 2008 |
| Externally published | Yes |
| Event | 9th International Federation on Automatic Control Conference on Intelligent Manufacturing Systems - 2008 - Szczecin, Poland Duration: 09.10.2008 → 10.10.2008 Conference number: 9 http://www.ifacims2019.com/ |
- Engineering - Fuzzy networks, inversion, noise reduction