Sliding mode observer‐based AC voltage sensorless model predictive control for grid‐connected inverters

Abstract

Recently, model predictive control has been widely used to control grid-connected inverters due to its advantages. However, the conventional model predictive control methods usually require two AC voltage and current sensors to sample the grid voltages and currents. Particularly, the DC voltage sensor is also required to calculate the values of the voltage vectors. The inverter will lose its stability once these sensors fail. Thus, in this study, to improve the operational reliability of the gridconnected inverters, a sliding mode observer-based AC voltage sensorless model predictive control is proposed. First, a sliding mode observer is designed to estimate the grid voltage. Next, a new adaptive compensation strategy is proposed to remove the phase and amplitude errors caused by the low-pass filter. The main novelty of this compensation strategy is that it is immune to the actual grid frequency. Therefore, the grid voltage can be identified accurately, even under frequency deviation conditions. Besides, the stability and parameter designing method of the sliding mode observer is also analysed to provide a theoretical basis for its implementation. Finally, based on the observed grid voltage, the AC voltage sensorless model predictive control is achieved. Detailed comparative experimental results show the validity of the proposed method.

Linear Active Disturbance Rejection Control Strategy with Known Disturbance Compensation for Voltage-Controlled Inverter

“…In practice, the derivation of capacitor voltage with a low-pass filter (LPF) is used to estimate the load current, but it needs the differential signals of the voltage. The observer, such as a disturbance observer [31] or sliding mode observer [32], is also an effective method to obtain the load current, but it needs to be designed separately, increasing the system complexity. In this paper, the LESO observation state is used to simplify the design of load current observation.…”

Dynamic sliding mode control of single‐stage boost inverter with parametric uncertainties and delay

“…Two-loop sliding mode control was suggested in [10], and a classic sliding mode controller was proposed in [11] to control the boost inverter. Also, in [12] a sliding mode control algorithm is designed for single-stage boost inverter. The sliding-mode control schemes presented in [10][11][12] achieve good steady-state results.…”

“…Also, in [12] a sliding mode control algorithm is designed for single-stage boost inverter. The sliding-mode control schemes presented in [10][11][12] achieve good steady-state results. However, have some disadvantages related to the required complex theory, the variable switching frequency and seem to be impractical because strict sufficient conditions with the coefficients in the sliding surfaces should be satisfied.…”

Coordinated power control withoutACvoltage sensing and active power filtering using interlinking converter with reduced interlinking power flow in a droop controlled islanded hybridAC‐DCmicrogrid

“…AC voltage sensor‐less control is extensively investigated in the literature for grid‐connected power converters, 22,25‐28 power factor correction converter, 29 and pulse width modulation (PWM) rectifiers, 23,24,30‐35 but it is not studied for the IC in HMG applications. This article explores and describes the control of IC for active power transferring between the subgrids without sensing the AC bus voltage.…”

“…In Reference 23, a sensorless control strategy with the insertion of an adaptive neural estimator into voltage‐oriented control of the PWM rectifier is proposed, even though this technique is effective it needs the network parameters to be adjusted online, which is difficult. State observer‐based techniques for the elimination of AC grid voltage sensors are presented in References 22,25‐28, which require the observer gains to be selected carefully for the system to be stable. Voltage sensorless techniques involving model predictive control of the converters are presented in References 30,31,33, but the issue is they require the complete model of the system to be computed which increases the computational intensity.…”