Frequency-Adaptive Current Controller Design Based on LQR State Feedback Control for a Grid-Connected Inverter under Distorted Grid

This paper proposes a frequency-adaptive current control design for a grid-connected inverter with an inductive–capacitive–inductive (LCL) filter to overcome the issues relating to both the harmonic distortion and frequency variation in the grid voltage. The current control scheme consists of full-state feedback control to stabilize the system and integral control terms to track the reference in the presence of disturbance and uncertainty. In addition, the current controller is augmented with resonant control terms to mitigate the harmonic component. The control scheme is implemented in the synchronous reference frame (SRF) to effectively compensate two harmonic orders at the same time by using only one resonant term. Moreover, to tackle the frequency variation issue in grid voltage, the frequency information which is extracted from the phase-locked loop (PLL) block is processed by a moving average filter (MAF) for the purpose of eliminating the frequency fluctuation caused by the harmonically distorted grid voltage. The filtered frequency information is employed to synthesize the resonant controller, even in the environment of frequency variation. To implement full-state feedback control for a grid-connected inverter with an LCL filter, all the state variables should be available. However, the increase in number of sensing devices leads to the rise of cost and complexity for hardware implementation. To overcome this challenge, a discrete-time full-state current observer is introduced to estimate all the system states. When the grid frequency is subject to variation, the discrete-time implementation of the observer in the SRF requires an online discretization process because the system matrix in the SRF includes frequency information. This results in a heavy computational burden for the controller. To resolve such a difficulty, a discrete-time observer in the stationary reference frame is employed in the proposed scheme. In the stationary frame, the discretization of the system model can be accomplished with a simple offline method even in the presence of frequency variation since the system matrix does not include the frequency. To select desirable gains for the full-state feedback controller and full-state observer, an optimal linear quadratic control approach is applied. To validate the practical effectiveness of the proposed frequency-adaptive control, simulation and experimental results are presented.