Voltage Sensorless Model Predictive Control for a Grid-Connected Inverter With <i>LCL</i> Filter

Nam, Nguyen Ngoc; Nguyen, Ngoc Duc; Yoon, Changwoo; Choi, M. Y.; Lee, Young Il

doi:10.1109/tie.2021.3050395

Cited by 51 publications

(28 citation statements)

References 24 publications

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“…To highlight the efficacy of the proposed control scheme, a proportional-integral controller (PI) [19] and an MPC developed [14] in earlier work are compared to the proposed control method. For a fair comparison, the PI controller gains are tuned according to symmetrical optimum in the former study [19], and feedforward terms are added to the controller.…”

Section: B Simulation Resultsmentioning

confidence: 99%

“…In the presence of LCL parameter uncertainties, the full-state and grid voltage (FSGV) estimator introduced in earlier work [14] cannot be used. Thus, in this section, a lumped disturbance observer is designed based on an FSGV estimator.…”

Section: Full-state Estimation and Disturbance Observer Designmentioning

confidence: 99%

“…This lumped disturbance observer will estimate the effects of LCL parameter uncertainties and grid impedance variations to remove the steady-state FSGV estimation error. First, the design procedure of the FSGV estimator from the aforementioned study [14] is described briefly.…”

Section: Full-state Estimation and Disturbance Observer Designmentioning

confidence: 99%

“…Recently, grid-voltage sensorless control has attracted much attention for interfacing renewable energy sources (RESs) to the utility grid [1]- [4], [6]- [14]. The primary purpose of grid voltage measurements is to extract the grid phase angle to synchronize the inverter to the utility grid.…”

Section: Introductionmentioning

confidence: 99%

“…This paper proposes a disturbance observer-based robust model predictive control for a voltage sensorless GCI with an LCL filter considering the parameter uncertainties and grid impedance variation explicitly. Unlike earlier work in this area [14], the inverter-side inductance levels and grid impedance variations are considered in this paper. It is essential to consider parameter uncertainties during the design of an estimator and controller for an LCL-filtered grid-connected inverter.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Disturbance Observer-Based Robust Model Predictive Control for a Voltage Sensorless Grid-Connected Inverter With an LCL Filter

et al. 2021

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This paper proposes a disturbance observer-based robust model predictive control (MPC) for a voltage sensorless grid-connected inverter with an inductive-capacitive-inductive (LCL) filter. A full-state estimator and a grid voltage observer are designed to reduce the number of sensors. A lumped disturbance observer, considering the parameter mismatch along with the grid impedance variation, is also designed to eliminate the steady-state error. A cost function, which consists of the error state and control input, is employed in the MPC design. Based on the Lyapunov stability, the full-state observer, voltage estimation, lumped disturbance observer, and the robust controller gains are obtained by solving an optimization problem based on linear matrix inequality (LMI). A frequency response analysis of the entire system is conducted to verify the reference tracking and disturbance rejection outcomes. As a result, the state and grid voltage observer outcomes converge to the actual values as rapidly as possible. The effectiveness of the proposed control method is demonstrated in comparison with the proportional-integral (PI) approach and with a controller recently proposed in the literature. Simulation and experimental results are presented to verify the effectiveness of the proposed method under LCL parameter uncertainties and grid impedance variations.INDEX TERMS Sensorless model predictive control (MPC), disturbance observer, three-phase inverters, inductive-capacitive-inductive (LCL)

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Section: B Simulation Resultsmentioning

confidence: 99%

Section: Full-state Estimation and Disturbance Observer Designmentioning

confidence: 99%

Section: Full-state Estimation and Disturbance Observer Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Disturbance Observer-Based Robust Model Predictive Control for a Voltage Sensorless Grid-Connected Inverter With an LCL Filter

et al. 2021

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Low‐Cost Data Glove Based on Deep‐Learning‐Enhanced Flexible Multiwalled Carbon Nanotube Sensors for Real‐Time Gesture Recognition

Yang

et al. 2022

Advanced Intelligent Systems

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With advancements in artificial intelligence, wearable motion recognition systems based on flexible nanomaterial sensors exhibit excellent potential for harmonious human–machine interaction. However, the sensing stability and demand of large‐scale arrays limit the application of flexible nanomaterial sensors. Herein, a data glove system based on simple multiwalled carbon nanotube (MWCNT) sensors and a lightweight deep‐learning algorithm to achieve accurate gesture recognition is proposed. A regional‐crack mechanism is introduced through the microspine structure to enhance the strain sensitivity. Moreover, an efficient signal processing strategy based on an adaptive wavelet threshold function to improve the robustness and anti‐interference of signals obtained from MWCNT sensors, which exhibit strong generalization and can be used in other nanomaterial strain sensor. Based on the depth‐wise separable convolution, a novel hybrid convolutional neural network (CNN) long short‐term memory (LSTM) model for gesture recognition is constructed. The proposed model achieves an average accuracy of 97.5% and recognition accuracy of 30 gestures with an average recognition time of 2.173 ms based on only five sensors. The fabricated data glove is a promising platform for low‐cost and wearable human–machine interaction that can be directly interfaced in applications such as robotic hands, smart cars, and first‐person shooting games.

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LCL‐filter resonance suppression in grid‐connected inverter based on strictly real positive plant strategy

Khan

Waseem

et al. 2022

Circuit Theory & Apps

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Resonance is one of the most significant challenges in a voltage source inverter interfaced with the grid through an LCL filter. The capacitor current (CC) damping control methodology is considered due to its high‐quality of grid injected current feature. It is widely accepted that the proportional CC feedback compensation damping method becomes ineffective at critical resonance frequency due to control loop delays and may result in an unstable system under grid impedance or filter parameters variations. A suitable differential compensator placed in the CC feedback path can address this issue with a trade‐off between robustness and noise rejection capability. This paper offers a different design method called parallel feedforward compensation (PFC) method, which builds an almost strictly real positive (ASRP) plant and realized damping with enhanced stability features. In the proposed alternative, a compensator consisting of a damping gain and a sampled delay is placed across the filter plant and filter CC feedback loop and the joint output of this augmented plant is then transmitted back at the reference point on the input side of the inverter to attenuate the undesirable resonance peak. The control response and stability performance analysis show that the suggested methodology offers a wide damping region, high robustness, and improved control performance. Simulation and experimental results are presented to confirm the theoretical findings.

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Voltage Sensorless Model Predictive Control for a Grid-Connected Inverter With LCL Filter

Cited by 51 publications

References 24 publications

Disturbance Observer-Based Robust Model Predictive Control for a Voltage Sensorless Grid-Connected Inverter With an LCL Filter

Disturbance Observer-Based Robust Model Predictive Control for a Voltage Sensorless Grid-Connected Inverter With an LCL Filter

Low‐Cost Data Glove Based on Deep‐Learning‐Enhanced Flexible Multiwalled Carbon Nanotube Sensors for Real‐Time Gesture Recognition

LCL‐filter resonance suppression in grid‐connected inverter based on strictly real positive plant strategy

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