STABILISATOR SISTEM TENAGA BERBASIS JARINGAN SYARAF TIRUAN BERULANG UNTUK SISTEM MESIN TUNGGAL
Abstract: In this paper,
recurrent neural network (RNN) is used to design power system stabilizer (PSS)
due to its advantage on the dependence not only on present input but also on
past condition. A RNN-PSS is able to capture the dynamic response of a system
without any delays caused by external feedback, primarily bythe internal
feedback loop in recurrent neuron. In this paper, RNNPSS consists of a
RNN-identifier and a RNN-controller. The RNN-Identifier functions as the
tracker of dynamics characteristics of the plant, while the RNN-controller is
used to damp the system’s low frequency oscillations. Simulation results using
MATLAB demonstrate that the RNNPSS can successfully damp out oscillation and
improve the performance of the system.
Penulis: Widi Aribowo
Kode Jurnal: jptkomputerdd100028
