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Adaptive Nonlinear Control of Reduced‐Part three‐Phase Shunt Active Power Filters
Author(s) -
Abouelmahjoub Younes,
Giri Fouad,
Abouloifa Abdelmajid,
Chaoui FatimaZahra,
Kissaoui Mohammed
Publication year - 2018
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.1681
Subject(s) - control theory (sociology) , harmonics , nonlinear system , three phase , ac power , robustness (evolution) , engineering , lyapunov function , voltage regulation , controller (irrigation) , power factor , voltage , computer science , control (management) , physics , agronomy , biochemistry , chemistry , quantum mechanics , artificial intelligence , biology , electrical engineering , gene
The problem of controlling reduced‐part three‐phase shunt active power filters is addressed in the presence of nonlinear loads. The control objective is twofold: (i) compensation of the current harmonics and the reactive power absorbed by the nonlinear load in order to ensure a satisfactory power factor correction (PFC) at the grid‐filter connection point; (2) regulation of the DC bus voltage at the inverter input. The considered control problem entails several difficulties including: (1) the high dimension and strong nonlinearity of the system; (ii) the numerous state variables that are inaccessible to measurements; (iii) the system parameter uncertainty. The problem is dealt with by designing a nonlinear adaptive controller with cascade structure including two control loops. The inner‐loop regulator is designed using the Lyapunov technique to ensure the PFC objective, while the outer‐loop involves a linear PI type control law for DC bus voltage regulation. The controller also includes an adaptive observer estimating the grid voltages and impedances parameters. The resulting control performances are formally analyzed using the averaging theory. Simulation results are presented illustrating the performances and the strong robustness of the proposed control strategy.