Equivalent input disturbance observer‐based ripple‐free deadbeat control for voltage regulation of a DC–DC buck converter

Yuan, Haibo; Kim, Young‐Bae

doi:10.1049/iet-pel.2019.0652

Cited by 8 publications

(5 citation statements)

References 39 publications

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“…Step 4.2-Verity exploitation phase: On the other hand, if 𝑇𝐹 > 0.5, there is no collision between objects. Then, acceleration of object is updated for iteration 𝑘 + 1 using (11).…”

Section: Self-tuning Pid Controller Of Dc-dc Buck Convertermentioning

confidence: 99%

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Optimized PID Controller of DC-DC Buck Converter based on Archimedes Optimization Algorithm

Fong,

Islam,

Ahmad

2023

IJRCS

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This research assesses the suitability of the Archimedes Optimization Algorithm (AOA) as a metaheuristic technique to fine-tune a PID controller in a closed-loop DC-DC buck converter. The converter's core function is to regulate output voltage, ensuring stability despite load fluctuations and input voltage changes. The operational effectiveness of the converter hinges significantly on the gain settings of the PID controller and determining the optimal gain setting for the PID controller is a non-trivial task. For robust performance, the PID controller necessitates optimal gain settings, attainable through metaheuristic optimization. The algorithm aids in identifying ideal proportional, integral, and derivative gains based on varying load conditions. Leveraging the metaheuristic algorithm, the PID controller is optimized to minimize voltage errors, reduce overshoot, and enhance response time. The proposed PID controller, optimized using AOA, is contrasted with PID controllers tuned via alternative algorithms including the hybrid Nelder-Mead method (AEONM), artificial ecosystem-based optimization (AEO), differential evolution (DE), and particle swarm optimizer (PSO). Performance evaluation involves injecting a voltage disturbance into the buck converter with load changes of up to 20%. Results demonstrate the superiority of the AOA-optimized PID controller in voltage recovery. It demonstrates a faster response time and outstanding voltage regulation performance, while also exhibiting minimal performance degradation during load changes. This study concludes that the AOA optimization algorithm surpasses other methods in tuning the PID controller for closed-loop DC-DC buck converters.

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“…Step 4.2-Verity exploitation phase: On the other hand, if 𝑇𝐹 > 0.5, there is no collision between objects. Then, acceleration of object is updated for iteration 𝑘 + 1 using (11).…”

Section: Self-tuning Pid Controller Of Dc-dc Buck Convertermentioning

confidence: 99%

“…The previous study about the disturbance analysis on the buck converter focused on input voltage variability and the injection of disturbance voltages [1], [11], [19]- [21]. In the presence of voltage fluctuations or disturbances, the primary objective of a buck converter is to sustain a stable output voltage without being affected by the disturbance.…”

mentioning

confidence: 99%

Optimized PID Controller of DC-DC Buck Converter based on Archimedes Optimization Algorithm

Fong,

Islam,

Ahmad

2023

IJRCS

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“…An optimized active disturbance rejection method with a reduced order generalized proportional integral observer (GPIO) is proposed in [90] for a buck converter to achieve optimized performance even with large disturbances. In [91], an equivalent input disturbance observer (EIDO) based method is proposed for voltage regulation of a buck converter against model uncertainties and output disturbances.…”

Section: ) Fast Response Capability Against Pplmentioning

confidence: 99%

Review on Advanced Control Technologies for Bidirectional DC/DC Converters in DC Microgrids

Vafamand

Chen

et al. 2021

IEEE J. Emerg. Sel. Topics Power Electron.

264

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DC microgrids encounter the challenges of constant power loads (CPLs) and pulsed power loads (PPLs), which impose the requirements of fast dynamics, large stability margin, high robustness that cannot be easily addressed by conventional linear control methods. This necessitates the implementation of advanced control technologies in order to significantly improve the robustness, dynamic performance, stability and flexibility of the system. This paper presents an overview of advanced control technologies for bidirectional dc/dc converters in DC microgrids. First, the stability issue caused by CPLs and the power balance issue caused by PPLs are discussed, which motivate the utilization of advanced control technologies for addressing these issues. Next, typical advanced control technologies including model predictive control, backstepping control, sliding mode control, passivitybased control, disturbance estimation techniques, intelligent control and nonlinear modeling approaches are reviewed. Then the applications of advanced control technologies in bidirectional DC/DC converters are presented for the stabilization of CPLs and accommodation of PPLs. Finally, advanced control techniques are explored in other high gain non-isolated (e.g., interleaved, multilevel, cascaded) and isolated converters (e.g., dual active bridge) for high power applications.

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“…The integral time-weighted absolute error (ITAE) method is utilized to tune the parameters of PI controllers for two designed converters, and the optimized parameters are listed in Table 2. What's more, the stability of the designed PI controllers was studied in our previous works [27], [28], and both converters can stably regulate the power output under an energy management strategy.…”

Section: 𝑢 𝐾 𝑒mentioning

confidence: 99%

A Real-Time Rule-Based Energy Management Strategy With Multi-Objective Optimization for a Fuel Cell Hybrid Electric Vehicle

et al. 2022

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Energy management strategy (EMS) has a great impact on securing fuel cell durability, battery charge sustenance, and fuel saving in fuel cell hybrid electric vehicles (FCHEVs). This study aims to develop EMS that can be applied in real-time to satisfy above conditions. Real time power separation was performed using rule-based EMS. A genetic algorithm (GA) was implemented to calculate the optimal battery charge/discharge criterion that simultaneously satisfies the minimum hydrogen consumption rate, battery charge rate preservation, and high fuel cell efficiency. The battery charge/discharge parameter values vary according to driving patterns, and in this paper, typical suburban, urban, and highway driving conditions are considered. For the real-time application of this research method, the effectiveness was demonstrated by applying the driving conditions of unknown patterns. The effect on the initial battery SOC on EMS was analyzed, and in order to verify the superiority of this method, it was compared and analyzed with EMS results using dynamic programming and fuzzy logic under the same driving cycles. The effectiveness of this research method was verified through simulation, and it was confirmed through experiments for real-time application. Since there is a limit to the experiment using an actual fuel cell vehicle, the experiment was performed using a fuel cell and battery. This method can be applied to real fuel cell vehicles in the same way.INDEX TERMS Battery charge sustenance, energy management, fuel cell hybrid electric vehicle, hydrogen consumption, multi-objective GA.

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Equivalent input disturbance observer‐based ripple‐free deadbeat control for voltage regulation of a DC–DC buck converter

Cited by 8 publications

References 39 publications

Optimized PID Controller of DC-DC Buck Converter based on Archimedes Optimization Algorithm

Optimized PID Controller of DC-DC Buck Converter based on Archimedes Optimization Algorithm

Review on Advanced Control Technologies for Bidirectional DC/DC Converters in DC Microgrids

A Real-Time Rule-Based Energy Management Strategy With Multi-Objective Optimization for a Fuel Cell Hybrid Electric Vehicle

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