Adaptive High-Gain Observer-Based Control for Grid-Tied LCL Filter Systems

Abstract

This paper presents the design and real-time implementation of a composite controller consisting of a state-feedback control law and high-gain observer for grid-tied inverter with <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LCL</i> filter. The state-feedback controller is designed in the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$dq$</tex-math></inline-formula> reference frame to stabilize the closed-loop system. High-gain observer serves as a disturbance observer to estimate a fictitious variable, representing the effect of model uncertainties and unknown disturbances, which is then canceled by the state-feedback controller. Thus, asymptotic regulation can be guaranteed under the composite controller even in the presence of parametric uncertainties and unknown inputs. High-gain observer has a rate of convergence that is dependent on its gain which is required to be large enough to ensure fast disturbance estimation, and then nominal performance recovery. However, high observer gain can lead to poor steady-state performances due to the effect of measurement noise. This concern is overcome in this work by using an existing adaptive technique to adjust the observer gain on-line. Moreover, the resulting high-gain observer is further simplified to provide a less-complex estimator and to show its integral action property. The performance of the composite controller was experimentally tested. The obtained results demonstrated the ability of the proposed controller to meet the nominal performance specifications while reducing the effect of measurement noise in steady-state.