Adaptive Critic Based Neurocontroller for Turbogenerators with Global Dual Heuristic Programming
This document has been relocated to http://scholarsmine.mst.edu/ele_comeng_facwork/841
There were 2 downloads as of 27 Jun 2016.
Abstract
Turbogenerators are nonlinear time varying systems. This paper presents the design of a neurocontroller for such a turbogenerator that augments/replaces the traditional automatic voltage regulator (AVR) and the turbine governor using a novel technique based on the adaptive critic designs (ACDs) with emphasis on global dual heuristic programming (GDHP). Simulation results are presented to show that the neurocontroller derived with the GDHP approach is robust and its performance is better when compared with that derived with other neural network technique, especially when system conditions and configuration changes.
This paper has been withdrawn.
