This paper compares two indirect adaptive neurocontrollers, namely a multilayer perceptron neurocontroller (MLPNC) and a radial basis function neurocontroller (RBFNC) to control a synchronous generator. The different damping and transient performances of two neurocontrollers are compared with those of conventional linear controllers, and analyzed based on the Lyapunov direct method.
Bibliographical noteFunding Information:
Manuscript received August 28, 2002; revised June 25, 2003. This work was supported in part by the National Science Foundation (NSF), under Grant ECS-0080764 and in part by the Duke Power Company, Charlotte, NC.
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Computer Networks and Communications
- Artificial Intelligence