Throttle valve control using an inverse local linear model tree based on a Fuzzy neural network
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
Authors
A robust throttle valve control has always been an 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 | 2008 7th IEEE International Conference on Cybernetic Intelligent Systems, CIS 2008 |
| Editors | Richard A. Comley |
| Number of pages | 6 |
| Publisher | IEEE - Institute of Electrical and Electronics Engineers Inc. |
| Publication date | 2008 |
| Pages | 234-239 |
| Article number | 4798943 |
| ISBN (print) | 978-1-4244-2914-1 |
| ISBN (electronic) | 978-1-4244-2915-8 |
| DOIs | |
| Publication status | Published - 2008 |
| Externally published | Yes |
| Event | 7th Institute of Electrical and Electronics Engineers International Conference on Cybernetic Intelligent Systems - CIS2008 - London, United Kingdom Duration: 09.09.2008 → 10.09.2008 Conference number: 7 http://www.cybernetic.org.uk/cis2008 |
- By-wire systems, Control loops, Control problems, Control strategies, Data measurements, Feed forwards, Feed-forward controllers, High orders, In controls, Inverse models, Local linear model trees, Noise effects, Simulated results, State variables, Throttle valves, Fuzzy neural networks, Intelligent control, Intelligent systems, Inverse problems, Three term control systems, Mathematical models
- Engineering