In this paper, we present a novel identification and control scheme, which is able to identify and to control a synchronous generator using a neural identifier. The generator is modelled as a full (eight) order system. A third order neural network is used to identify a reduced order model of this generator. Moreover, a discontinuous control law based on the neural identifier is designed using the block control technique, in order to track reference signals and rejects external disturbances produced by generator terminal short circuits. Simulation results, using the full order model of the generator, are presented in order to test the applicability of the proposed approach.
|Number of pages
|Dynamics of Continuous, Discrete and Impulsive Systems Series B: Applications and Algorithms
|Published - Feb 2008
- Block control
- Recurrent high order neural networks