Cascaded model‐free predictive control for single‐phase boost power factor correction converters

Gu, Jiayuan; Li, Hongmei; Zhang, Hengguo; Pan, Cai‐Yuan; Luan, Zhiyuan

doi:10.1002/rnc.5526

Cited by 10 publications

(3 citation statements)

References 39 publications

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“…The increased error due to the second variation is trivial in comparison to the rest mismatches in Table 2. Cascaded model-free predictive control [20] has been proposed for the single-phase boost power factor correction converter. A unified ultra-local model has been used for the continuous conduction mode (CCM) and discontinuous conduction mode (DCM) of the power converter.…”

Section: E Computation Time Of the Control Algorithmmentioning

confidence: 99%

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Model-Free Predictive Control and Its Applications

2022

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Predictive control offers many advantages such as simple design and a systematic way to handle constraints. Model predictive control (MPC) belongs to predictive control, which uses a model of the system for predictions used in predictive control. A major drawback of MPC is the dependence of its performance on the model of the system. Any discrepancy between the system model and actual plant behavior will greatly affect the performance of the MPC. Recently, model-free approaches have been gaining attention because they are not dependent on the system model parameters. To obtain the advantages of both a model-free approach and predictive control, model-free predictive control (MFPC) is being explored and reported in the literature for different applications such as power electronics and electric drives. This paper presents an overview of model-free predictive control. A comprehensive review of the application of MFPC in power converters, electric drives, power systems, and microgrids is presented in this paper. Moreover, challenges, opportunities, and emerging trends in MFPC are also discussed in this paper.

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Section: E Computation Time Of the Control Algorithmmentioning

confidence: 99%

“…Model-free predictive control for current regulation of a three-phase inverter [18] Model-free neural-network-based predictive controller for a three-phase inverter [19] Cascaded model-free predictive control for a boost converter [20] Model-free predictive control for pulse width modulation rectifiers…”

Section: Mfpc For Power Converters Referencementioning

confidence: 99%

Model-Free Predictive Control and Its Applications

2022

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“…There are many works in the literature focusing on predictive current control 6,17,35 . A cascaded model-free predictive control approach based on the unified ultra-local model is proposed in reference 36 for single-phase boost power factor correctors are presented to increase control performance and resilience. With a set switching frequency and dead-time compensation, a model predictive current control is presented to lower the grid-side current's total harmonic distortion (THD) in reference 37 .…”

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confidence: 99%

A dSPACE-based implementation of ANFIS and predictive current control for a single phase boost power factor corrector

Babes,

Latrèche,

Bouafassa

et al. 2024

Sci Rep

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This paper presents an innovative control scheme designed to significantly enhance the power factor of AC/DC boost rectifiers by integrating an adaptive neuro-fuzzy inference system (ANFIS) with predictive current control. The innovative control strategy addresses key challenges in power quality and energy efficiency, demonstrating exceptional performance under diverse operating conditions. Through rigorous simulation, the proposed system achieves precise input current shaping, resulting in a remarkably low total harmonic distortion (THD) of 3.5%, which is well below the IEEE-519 standard threshold of 5%. Moreover, the power factor reaches an outstanding 0.990, indicating highly efficient energy utilization and near-unity power factor operation. To validate the theoretical findings, a 500 W laboratory prototype was implemented using the dSPACE ds1104 digital controller. Steady-state analysis reveals sinusoidal input currents with minimal THD and a power factor approaching unity, thereby enhancing grid stability and energy efficiency. Transient response tests further demonstrate the system’s robustness against load and voltage fluctuations, maintaining output voltage stability within an 18 V overshoot and a 20 V undershoot during load changes, and achieving rapid response times as low as 0.2 s. Comparative evaluations against conventional methods underscore the superiority of the proposed control strategy in terms of both performance and implementation simplicity. By harnessing the strengths of ANFIS-based voltage regulation and predictive current control, this scheme offers a robust solution to power quality issues in AC/DC boost rectifiers, promising substantial energy savings and improved grid stability. The results affirm the potential of the proposed system to set new benchmarks in power factor correction technology.

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