In this paper, a Radial Basis Function neural network based AVR is proposed. A control strategy which generates local linear models from a global neural model on-line is used to derive controller feedback gains based on the Generalised Minimum Variance technique. Testing is carried out on a micromachine system which enables evaluation of practical implementation of the scheme. Constraints imposed by gathering training data, computational load, and memory requirements for the training algorithm are addressed.
|Number of pages||6|
|Journal||IEEE Transactions on Energy Conversion|
|Publication status||Published - 1999|
ASJC Scopus subject areas
- Energy Engineering and Power Technology
- Fuel Technology
- Electrical and Electronic Engineering