An Adaptive Robust Predictive Current Control for Three-Phase Grid-Connected Inverters

Espı́, J.M.; Castelló, J.; Garcı́a-Gil, R.; Garcerá, G.; Figueres, E.

doi:10.1109/tie.2010.2089945

Cited by 156 publications

(73 citation statements)

References 37 publications

(21 reference statements)

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“…The structure of a typical adaptive controller is shown in Figure 31. In the literature, some credible research articles and state-of-the-art techniques for adaptive controllers are found in [14,37,53,55,113,[122][123][124][125]. These controllers are applicable for both dynamic as well as static processes.…”

Section: Adaptive Controllersmentioning

confidence: 99%

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Digital Control Techniques Based on Voltage Source Inverters in Renewable Energy Applications: A Review

et al. 2018

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Abstract:In the modern era, distributed generation is considered as an alternative source for power generation. Especially, need of the time is to provide the three-phase loads with smooth sinusoidal voltages having fixed frequency and amplitude. A common solution is the integration of power electronics converters in the systems for connecting distributed generation systems to the stand-alone loads. Thus, the presence of suitable control techniques, in the power electronic converters, for robust stability, abrupt response, optimal tracking ability and error eradication are inevitable. A comprehensive review based on design, analysis, validation of the most suitable digital control techniques and the options available for the researchers for improving the power quality is presented in this paper with their pros and cons. Comparisons based on the cost, schemes, performance, modulation techniques and coordinates system are also presented. Finally, the paper describes the performance evaluation of the control schemes on a voltage source inverter (VSI) and proposes the different aspects to be considered for selecting a power electronics inverter topology, reference frames, filters, as well as control strategy.

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Section: Adaptive Controllersmentioning

confidence: 99%

“…Field programmable gate array-based implementation (FPGA) [55][56][57] In reliable scientific research, generally, DSP is used. Fixed point arithmetic and floating-point algorithms are mostly used in implementing the digital control technique by DSP.…”

mentioning

confidence: 99%

Digital Control Techniques Based on Voltage Source Inverters in Renewable Energy Applications: A Review

et al. 2018

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“…At the same time, the current observer is used to predict the next beat current in [10,21,22], and the current reference is predicted in advance to compensate for the delay. In [10,21], the current predictive algorithm based on repetitive control observer is proposed, which solves the problem of the current instability caused by the control delay and improves the current predictive precision.…”

Section: Journal Of Electrical and Computer Engineeringmentioning

confidence: 99%

“…However, this method does not involve the dynamic analysis. In [22], an improved deadbeat current control scheme with a novel adaptive self-tuning load model is proposed. An improved deadbeat current controller with delay compensation is used to achieve high bandwidth current control characteristic, which compensates for the delay of the total system.…”

Section: Journal Of Electrical and Computer Engineeringmentioning

confidence: 99%

A Double Update PWM Method to Improve Robustness for the Deadbeat Current Controller in Three-Phase Grid-Connected System

Yang

Chen

Luo

et al. 2018

Journal of Electrical and Computer Engineering

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In the grid-connected inverter based on the deadbeat current control, the filter inductance variation and single update PWM affect the distortion of the grid current, stability, and dynamic of the system. For this, a double update PWM method for the deadbeat current controller in three-phase grid-connected system is proposed, which not only effectively decreases the grid current distortion and control delay, but also improves the system stability and dynamic response speed due to reducing the characteristic root equation order of the closed-loop transfer function. The influence of the filter inductance deviation coefficient on the system performance is analyzed. As a conclusion, the corresponding filter inductance deviation coefficient in the system critical stability increases with increase in the parasitic resistance of the filter inductance and line equivalent resistance and decreases with increase in the sampling frequency. Considering the system stability and dynamic response, the optimal range of the control parameters is acquired. Simulation and experimental results verify the effectiveness of the proposed method.

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“…However, a major challenge of the direct-current-based vector control mechanism is that no well-established systematical approach to tuning the PI controller gains exists, so that optimal DCC is hard to obtain. Other control methods have also been developed recently, direct power control [24][25][26] and predictive current control [27][28][29] in particular. Notwithstanding their merits, all these control methods show some limitations.…”

Section: Fig 1 Application Of Grid-connected Rectifier/inverter In mentioning

confidence: 99%

Artificial Neural Networks for Control of a Grid-Connected Rectifier/Inverter Under Disturbance, Dynamic and Power Converter Switching Conditions

Fairbank

Johnson

et al. 2014

IEEE Trans. Neural Netw. Learning Syst.

127

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This is the accepted version of the paper.This version of the publication may differ from the final published version. Permanent repository link City Research OnlineAbstract --Three-phase grid-connected converters are widely used in renewable and electric power system applications. Traditionally, grid-connected converters are controlled with standard decoupled d-q vector control mechanisms. However, recent studies indicate that such mechanisms show limitations in their applicability to dynamic systems. This paper investigates how to mitigate such restrictions using a neural network to control a grid-connected rectifier/inverter. The neural network implements a dynamic programming algorithm and is trained by using backpropagation through time. To enhance performance and stability under disturbance, additional strategies are adopted, including the use of integrals of error signals to the network inputs and the introduction of grid disturbance voltage to the outputs of a well-trained network. The performance of the neural network controller is studied under typical vector control conditions and compared against conventional vector control methods, which demonstrates that the neural vector control strategy proposed in this paper is effective. Even in dynamic and power converter switching environments, the neural vector controller shows strong ability to trace rapidly changing reference commands, tolerate system disturbances, and satisfy control requirements for a faulted power system.

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An Adaptive Robust Predictive Current Control for Three-Phase Grid-Connected Inverters

Cited by 156 publications

References 37 publications

Digital Control Techniques Based on Voltage Source Inverters in Renewable Energy Applications: A Review

Digital Control Techniques Based on Voltage Source Inverters in Renewable Energy Applications: A Review

A Double Update PWM Method to Improve Robustness for the Deadbeat Current Controller in Three-Phase Grid-Connected System

Artificial Neural Networks for Control of a Grid-Connected Rectifier/Inverter Under Disturbance, Dynamic and Power Converter Switching Conditions

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