Abstract
This paper introduces a fuzzy neural based adaptive controller for simultaneous stabilization and robust performance of a family of plants. The family of plants may be attained from linearization of a nonlinear plant around different operating points or large parameter variations in a given plant. The main idea is to design a sequence of controllers corresponding to the different plants utilizing any standard control design. Thereafter, the obtained controllers will form the basis of the knowledge base of a fuzzy controller capable of deriving a desired crisp output through its inference engine. A neural network is utilized to derive a fuzzy model of the plant and to generate the rule base for the fuzzy logic controller through training. The effectiveness of this new scheme is verified on a smart structure with piezoceramic sensors and actuators.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 575-579 |
| Number of pages | 5 |
| Journal | Proceedings of the American Control Conference |
| Volume | 1 |
| State | Published - 1994 |
| Event | Proceedings of the 1994 American Control Conference. Part 1 (of 3) - Baltimore, MD, USA Duration: Jun 29 1994 → Jul 1 1994 |
ASJC Scopus subject areas
- Electrical and Electronic Engineering