Reinforcement learning based backstepping control of power system oscillations

Ali Karimi, Sara Eftekharnejad, Ali Feliachi

Research output: Contribution to journalArticlepeer-review

19 Scopus citations


This paper proposes a reinforcement learning based backstepping control technique for damping oscillations in electric power systems using the generators excitation systems. Decentralized controllers are first designed using the backstepping technique. Then, reinforcement learning is used to tune the gains of these controllers to adapt to various operating conditions. Simulation results for a two area power system show that the proposed control technique provides better damping than (i) conventional power system stabilizers and (ii) backstepping fixed gain controllers.

Original languageEnglish (US)
Pages (from-to)1511-1520
Number of pages10
JournalElectric Power Systems Research
Issue number11
StatePublished - Nov 2009
Externally publishedYes


  • Backstepping control
  • Power system dynamics
  • Reinforcement learning

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering


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