Mk. Elsherbiny et al., SPEED DEVIATION DRIVEN ADAPTIVE NEURAL-NETWORK-BASED POWER-SYSTEM STABILIZER, Electric power systems research, 38(3), 1996, pp. 169-175
The paper presents an online adaptive artificial neural network (ANN)
based power system stabilizer (PSS). The proposed controller is first
trained offline using a pole placement based state feedback gain techn
ique at different operating points. The trained ANN parameters (weight
s and biases) are updated and tuned online using the speed deviation a
s the reinforcement signal. The proposed PSS is tested at different op
erating conditions and a variety of regulator gains. The digital resul
ts validate the effectiveness and reliability of the new PSS in terms
of fast system response under different loading conditions compared wi
th the conventional PI controller and the modern control theory approa
ch of pole placement.