HYBRID ADAPTIVE TYPE-2 FUZZY TRACKING CONTROL OF CHAOTIC OSCILLATION DAMPING OF POWER SYSTEMS


Zirkohi M. M., Kumbasar T., Lin T.

ASIAN JOURNAL OF CONTROL, cilt.19, sa.3, ss.1114-1125, 2017 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 19 Sayı: 3
  • Basım Tarihi: 2017
  • Doi Numarası: 10.1002/asjc.1454
  • Dergi Adı: ASIAN JOURNAL OF CONTROL
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.1114-1125
  • Anahtar Kelimeler: Type-2 fuzzy system, Chaotic system, Sliding mode control, Power system, Moving sliding surface, SLIDING-MODE CONTROL, TIME CONTROL, DESIGN
  • İstanbul Teknik Üniversitesi Adresli: Evet

Özet

In this paper a novel hybrid direct/indirect adaptive fuzzy neural network (FNN) moving sliding mode tracking controller for chaotic oscillation damping of power systems is developed. The proposed approach is established by providing a tradeoff between the indirect and direct FNN controllers. It is equipped with a novel moving sliding surface (MSS) to enhance the robustness of the controller against the present system uncertainties and unknown disturbances. The major contribution of the paper arises from the new simple tuning idea of the sliding surface slope and intercept of the MSS. This study is novel because the approach adopted tunes the sliding surface slope and intercept of MSS using two simple rules simultaneously. One advantage of the proposed approach is that the restriction of knowing the bounds of uncertainties is also removed due to the adaptive mechanism. Moreover, the stability of the control system is also presented. The proposed controller structure is successfully employed to damp the complicated chaotic oscillations of an interconnected power system, when such oscillations can be made by load perturbation of a power system working on its stability edges. Comparative simulation results are presented, which confirm that the proposed hybrid adaptive type-2 fuzzy tracking controller shows superior tracking performance.