Weighted-PSO Applied to Tune Sliding Mode Plus PI Controller Applied to a Boost Converter in a PV System

Gil, Gloria Milena Vargas; Rodrigues, Lucas Lima; Inomoto, Roberto Sussumu; Filho, Alfeu J. Sguarezi; Monaro, Renato M.

doi:10.3390/en12050864

Cited by 13 publications

(4 citation statements)

References 48 publications

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“…In the state-of-the-art SOO [26][27][28]30] and MOO [29] based control techniques, evolutionary algorithms are considered as an offline or online tuning tool. In other words, in [26][27][28]30], a basic controller, which can be PI or PID is used to generate a continuous signal valued in the interval 𝑢 ∈ [0,1] and then applied to the PWM block to generate the switching signal; and evolutionary approaches are utilized to tune the gains and characteristics of the basic controller.…”

Section: Closed-loop DC Mg System With Nsbga -Ii Controllermentioning

confidence: 99%

“…The main distinguishing feature of the developed approach over the state-of-the-art results is that it uses the MOO to generate the pulsing signal of converters without the need for the PWM. Thereby, the suggested topology is different from state-of-the-art methods [26][27][28][29][30]. The proposed approach utilizes the non-dominating sorting binary genetic algorithm (NSBGA-II).…”

Section: Introductionmentioning

confidence: 99%

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Intelligent Multiobjective NSBGA-II Control of Power Converters in DC Microgrids

Vafamand

Zarei

et al. 2021

IEEE Trans. Ind. Electron.

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Section: Closed-loop DC Mg System With Nsbga -Ii Controllermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Intelligent Multiobjective NSBGA-II Control of Power Converters in DC Microgrids

Vafamand

Zarei

et al. 2021

IEEE Trans. Ind. Electron.

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“…The reference current is given by an enhanced P&O MPPT algorithm. A constant DC source is utilized because it simplifies the analysis, giving the possibility of representing solar PV systems with a battery charge or solar PV systems with a second energy conversion stage [11]. The second stage is composed of a DC source connected to the WFS via a second DC-DC power converter.…”

Section: System Description and Modelingmentioning

confidence: 99%

New Optimal Control of Permanent Magnet DC Motor for Photovoltaic Wire Feeder Systems

Babes¹,

Boutaghane²,

Hamouda³

et al. 2020

JESA

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This article aims to improve the permanent magnet DC (PMDC) motor performance for photovoltaic (PV) wire-feeder systems (PVWFSs) of arc welding machines. The considered technique is designed by direct speed control based on optimal Fractional-order Fuzzy PID FO-Fuzzy-PID controller. The purpose is to ensure optimal control of wire feed speed reference to reduce torque ripples and hence, the performance of the WFS is improved. The dynamic reaction of the proposed solar PVWFS relies upon the scaling factors of FO-Fuzzy-PID controller, which are optimized by using teaching-learning algorithm based on Particle Swarm Optimization (PSO) method. The maximum power point tracking (MPPT) is achieved using an intelligent FO-Fuzzy-PID current controller based Perturb and Observe (P&O) MPPT algorithm. The PVWFS system incorporating the proposed method is tested and compared with the conventional PID control scheme under different weather conditions. The simulation of the proposed system by MATLAB\SIMULINK is carried out. The simulation results indicate the effectiveness of the considered control strategy in terms of the reduction in torque oscillations, optimizing electrical power and wire feed speed.

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“…Techniques such as BCT and SMC are known for their robustness and good performance. However, due to their nonlinear nature, these methods often result in higher computational costs [14,27,[27][28][29][30]. On the other hand, MPCs with small receding horizons and unconstrained control laws offer the advantage of lower computational costs.…”

Section: Introductionmentioning

confidence: 99%

Fake algebraic Riccati equation applied to model predictive control for doubly fed induction generator direct power control

Rodrigues

Velasquez

D.³

et al. 2023

IET Electric Power Appl

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Model Predictive Control (MPC) and Direct Power Control (DPC) are widely used in Doubly Fed Induction Generator (DFIG) applications. However, in the context of DPC‐based MPC for DFIG, there has been a lack of literature focusing on the design of the MPC parameters. In this way, this article introduces a novel technique for designing weighing matrices in Direct Power Model Predictive Control using the Fake Algebraic Riccati Equation (FARE). As FARE is associated with the infinite receding horizon, a small receding horizon can be designed without compromising the robustness. Furthermore, this article presents a computationally efficient linear state‐space model for DPC that, when combined with a small receding horizon FARE design, offers a controller with low computational cost and robustness. The proposed theory is validated through experimental results under normal operation, variable speed operation, and parameter variations. Additionally, the proposed controller is compared to other MPC approaches.

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Weighted-PSO Applied to Tune Sliding Mode Plus PI Controller Applied to a Boost Converter in a PV System

Cited by 13 publications

References 48 publications

Intelligent Multiobjective NSBGA-II Control of Power Converters in DC Microgrids

Intelligent Multiobjective NSBGA-II Control of Power Converters in DC Microgrids

New Optimal Control of Permanent Magnet DC Motor for Photovoltaic Wire Feeder Systems

Fake algebraic Riccati equation applied to model predictive control for doubly fed induction generator direct power control

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