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Robust event‐triggered output feedback learning algorithm for voltage source inverters with unknown load and parameter variations
Author(s) -
Vamvoudakis Kyriakos G.,
Pour Safaei Farshad R.,
Hespanha João P.
Publication year - 2019
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.4565
Subject(s) - control theory (sociology) , voltage source , observer (physics) , voltage , computer science , filter (signal processing) , controller (irrigation) , inverter , inductance , control (management) , engineering , physics , agronomy , quantum mechanics , artificial intelligence , electrical engineering , computer vision , biology
Summary We consider the output feedback event‐triggered control of an off‐grid voltage source inverter (VSI) with unknown inductance‐capacitance ( L − C ) filter dynamics and connected load in the presence of an input disturbance acting at the inverter. Due to uncertain dynamics and unmodeled parameters in the L − C filter connected to the VSI, we use an adaptive observer to reconstruct the system's states by measuring only the voltage at the output. The control mechanism is constructed based on an impulsive actor/critic framework that approximates the cost, the event‐triggered controller, and the worst case disturbance and generates the desired AC output with the least energy dissipation. We provide rigorous stability proofs and illustrate the applicability of our results through a simulation example.