Digital Average Voltage/Digital Average Current Predictive Control for Switching DC–DC Converters

Zhou, Guohua; Mao, Guihua; Zhao, Hongbo; Zhang, Wei; Xu, Shungang

doi:10.1109/jestpe.2018.2868974

Cited by 24 publications

(9 citation statements)

References 24 publications

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“…In this section, a generalised tuning formula for the control horizon of one is obtained when there are no active constraints present. Using (19) and 20, we can place the closed-loop poles at the desired location which can be solved analytically. However, it is not guaranteed that the closed-loop poles with the desired specification can be placed arbitrarily.…”

Section: Generalised Predictive Controlmentioning

confidence: 99%

“…Dahlin PID and Bányász/Keviczky PID controllers, based on the recursive least‐squares estimation are implemented to study the robustness and output voltage regulation for the DC–DC buck converter. Advanced control systems such as sliding mode control [16], adaptive control [17], optimised pole‐zero‐cancellation using non‐linear least‐squares estimation [18], predictive digital average voltage/digital average current control [19], and MPC [20, 21] are already implemented for power converters. The MPC controller has also been implemented to reduce cross‐regulation in the single‐inductor dual‐output buck converter [22] and to improve the performance of a pre‐compensated power converter [23].…”

Section: Introductionmentioning

confidence: 99%

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Pre‐computed GPC of a DC–DC buck converter

Manjari

Majhi

Ramana

2019

IET Circuits, Devices & Systems

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This study presents the control mechanism of a DC-DC buck converter using generalised predictive control by approximating the plant model to a stable first-order plus dead time (FOPDT) model. As most of the higher order plant dynamics can be represented by an FOPDT model, this study is limited only to a stable FOPDT dynamics system. In this work, a relation between FOPDT model parameters and weights of the cost function is derived. The controller design procedure is then verified by implementing voltage mode control of the DC-DC buck converter in the case of inactive constraints. Jury's stability criteria are used to analyse the stability of the closed-loop system. The implemented algorithm is then verified using simulation in MATLAB/Simulink, as well as the hardware implementation of the pre-computed control algorithm.

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Section: Generalised Predictive Controlmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Pre‐computed GPC of a DC–DC buck converter

Manjari

Majhi

Ramana

2019

IET Circuits, Devices & Systems

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“…The associate editor coordinating the review of this manuscript and approving it for publication was Ali Raza . and controller, such as proposing sophisticated digital pulsewidth modulation (PWM) techniques to improve power efficiency in [2] and enhance transient response in [3], mainstream research also emphasizes dealing with the effects of sampling and computation delays and nonlinearities [2], [3], enhancing the characteristics of individual functional block and control law [4], [5], and optimizing system performance [6], [7]. Reference [2] proposes a digital PWM and low-power self-tracking zero current detector that can achieve high linearity and low power consumption.…”

Section: Introductionmentioning

confidence: 99%

“…Reference [5] proposes a digital predictive control algorithm for boost-type power factor corrector with the peak-to-peak inductor current estimated by a triangular modulation-based predictive control and a known value of output inductor. In [6], a digital average voltage and digital average current predictive control achieves a high output voltage accuracy, wide stability range, and fast transient response. In [7], the effective resolution of the PWM is enhanced by using a dithering technique on an ''SoC FPGA'' that can reduce peak output voltage ripple and lower switching frequency subharmonics.…”

Section: Introductionmentioning

confidence: 99%

Experimental Assessment of a Tiny AI-Empowered Output Filter Parameter Extraction Framework for Digital Power

et al. 2023

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An experimental assessment of a ''plug-and-play'' tiny artificial-intelligence-empowered output filter parameter extraction framework for digital power is presented. The framework can be incorporated into an existing digital controller to perform online parameter extraction without adding extra sensors or modifying the power conversion stage. The idea is based on firstly transferring the control from the default control law to the framework, which consists of a predefined control law to perform output regulation for a few switching cycles, then introducing a small-signal perturbation into the control signal, and finally utilizing a long short-term memory (LSTM) network to recognize the dynamic response of the control signal to perform either regression or classification of filter parameters. The LSTM network is trained with a reconfigurable output filter. The proposed framework has been successfully evaluated on a 240W, 100V/48V buck DC/DC converter prototype. The framework's performance is studied by extracting the parameters of a second-order output filter and a fourth-order output filter. For the second-order output filter, the root-mean-square errors (RMSEs) in performing the filter inductor and capacitor regressions are 2.35% and 2.25%, respectively, and the F1-scores in classifying the inductance and capacitance are 0.805 and 0.815, respectively. The framework occupies 0.93% of the memory space of the controller with 512kB flash memories. The extraction time is 17.3ms. For the fourth-order filter, the maximum RMSEs in performing the regression of the filter inductors and capacitors are 2.04% and 6.49%, respectively. The framework occupies 3.62% of the memory space and the extraction time is 328ms.

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“…Furthermore, electronic converters must sometimes control the injected harmonic components, often reaching high frequencies, as in the case of active filters [29]- [31], stand-alone inverters [32], [33], power amplifiers in audio systems [34], or compensation of the PWM voltage distortion [35]- [37]. In the same way, some converters are required to achieve very fast dynamics in order to track the reference or quickly reject the load disturbance, for example in the case of power supplies [38]- [40] and front-end rectifiers [41]. In all these occasions, the system should be modelled as a discrete one and discrete control methods should be applied [17], [20], [24].…”

Section: Introductionmentioning

confidence: 99%

Control Design and Stability Analysis of Power Converters: The Discrete Generalized Bode Criterion

et al. 2021

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For the controller design and stability analysis of power electronic converters, the Bode stability criterion and its subsequent revisions are the most practical tools. However, even though the control of the power converter is usually implemented in a microprocessor, none of these methods is infallible when applied to a discrete system. This paper therefore proposes a new stability criterion, named the Discrete Generalized Bode Criterion (DGBC). This method is based on the Nyquist criterion but developed from the open-loop Bode diagram, evaluated also at 0 Hz and at the Nyquist frequency. The proposed criterion combines the advantages of the Nyquist and Bode criteria, since it is always applicable and provides an interesting and useful tool for the controller design process. The method is applied to design an active damping control of an inverter with LCL filter, showing how the proposed criterion accurately predicts stability, in contrast to the existing Bode criteria. The theoretical analysis is validated through experimental results performed with a three-phase inverter and an LCL filter. INDEX TERMS Active damping control, control design, frequency domain analysis, LC-filtered voltage source inverter (VSI), stability criteria.

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Digital Average Voltage/Digital Average Current Predictive Control for Switching DC–DC Converters

Cited by 24 publications

References 24 publications

Pre‐computed GPC of a DC–DC buck converter

Pre‐computed GPC of a DC–DC buck converter

Experimental Assessment of a Tiny AI-Empowered Output Filter Parameter Extraction Framework for Digital Power

Control Design and Stability Analysis of Power Converters: The Discrete Generalized Bode Criterion

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