TY - JOUR
T1 - Flyback CCM inverter for AC module applications
T2 - iterative learning control and convergence analysis
AU - Lee, Sung Ho
AU - Kim, Minsung
N1 - Publisher Copyright:
© 2016 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2017/12/2
Y1 - 2017/12/2
N2 - This paper presents an iterative learning controller (ILC) for an interleaved flyback inverter operating in continuous conduction mode (CCM). The flyback CCM inverter features small output ripple current, high efficiency, and low cost, and hence it is well suited for photovoltaic power applications. However, it exhibits the non-minimum phase behaviour, because its transfer function from control duty to output current has the right-half-plane (RHP) zero. Moreover, the flyback CCM inverter suffers from the time-varying grid voltage disturbance. Thus, conventional control scheme results in inaccurate output tracking. To overcome these problems, the ILC is first developed and applied to the flyback inverter operating in CCM. The ILC makes use of both predictive and current learning terms which help the system output to converge to the reference trajectory. We take into account the nonlinear averaged model and use it to construct the proposed controller. It is proven that the system output globally converges to the reference trajectory in the absence of state disturbances, output noises, or initial state errors. Numerical simulations are performed to validate the proposed control scheme, and experiments using 400-W AC module prototype are carried out to demonstrate its practical feasibility.
AB - This paper presents an iterative learning controller (ILC) for an interleaved flyback inverter operating in continuous conduction mode (CCM). The flyback CCM inverter features small output ripple current, high efficiency, and low cost, and hence it is well suited for photovoltaic power applications. However, it exhibits the non-minimum phase behaviour, because its transfer function from control duty to output current has the right-half-plane (RHP) zero. Moreover, the flyback CCM inverter suffers from the time-varying grid voltage disturbance. Thus, conventional control scheme results in inaccurate output tracking. To overcome these problems, the ILC is first developed and applied to the flyback inverter operating in CCM. The ILC makes use of both predictive and current learning terms which help the system output to converge to the reference trajectory. We take into account the nonlinear averaged model and use it to construct the proposed controller. It is proven that the system output globally converges to the reference trajectory in the absence of state disturbances, output noises, or initial state errors. Numerical simulations are performed to validate the proposed control scheme, and experiments using 400-W AC module prototype are carried out to demonstrate its practical feasibility.
KW - interleaved technique
KW - iterative learning controller
KW - Microinverter
KW - nonlinear averaged model
UR - https://www.scopus.com/pages/publications/85000607320
U2 - 10.1080/00207179.2016.1263759
DO - 10.1080/00207179.2016.1263759
M3 - Article
AN - SCOPUS:85000607320
SN - 0020-7179
VL - 90
SP - 2677
EP - 2691
JO - International Journal of Control
JF - International Journal of Control
IS - 12
ER -