An adaptive backstepping control to ensure the stability and robustness for boost power converter in DC microgrids

Zhang, Zehua; Song, Guanyu; Zhou, Jiyao; Zhang, Xiaolu; Yang, Bowei; Liu, Chang; Guerrero, Josep M.

doi:10.1016/j.egyr.2022.02.024

Cited by 18 publications

(9 citation statements)

References 32 publications

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“…The final control input d of the converter is derived according to the initial coordinate transformation. For converters of the NMP system class, the coordinate transformation is used for full feedback linearisation, by defining the new state as the total stored energy, to avoid the indirect voltage control through current regulation, which leads to slow response and overshoot [61,62]. The generic structure of the backstepping control applied in a boost DC/DC converter, including the coordinate transformation, is presented in Figure 7.…”

Section: Backstepping Controlmentioning

confidence: 99%

Review of Modern Control Technologies for Voltage Regulation in DC/DC Converters of DC Microgrids

Korompili

Monti

2023

Energies

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This paper provides an overview of modern feedback control methods for the voltage regulation in DC/DC converters of DC microgrids. Control objectives and practical restrictions are defined and used as indicators for the analysis and performance assessment of the control methods. After presenting the concept of each control method, the advantages and limitations in the converter applications are discussed. The main conclusions of this overview can be used as recommendations for the selection of the suitable control method according to the control requirements in the DC microgrid. The low robustness against disturbances is a major issue in all control methods. For the enhancement of the robustness of the feedback control methods, three approaches are reviewed. Applications of these approaches in DC/DC converters are compared with regard to the achieved disturbance rejection and the related cost of nominal performance degradation. The disturbance/uncertainty estimation and attenuation (DUEA) framework appears to be the most promising approach to compromising these opposing control objectives. This overview is presented for a general DC/DC converter, without any additional control design requirement imposed by a specific converter plant. This allows the generalisation of the conclusions of the performance assessment, which can facilitate the application of the control methods in similar systems, such as in AC/DC converters or motor drives.

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Section: Backstepping Controlmentioning

confidence: 99%

Review of Modern Control Technologies for Voltage Regulation in DC/DC Converters of DC Microgrids

Korompili

Monti

2023

Energies

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“…Backstepping control (BSC) method can reach desirable prospects and provide better stability insurance for the operation [33,34]. Adaptive BSC (ABSC) includes the benefits of the conventional backstepping method; also, it has been improved in dynamics by the Lyapunov stability characteristics, leading to a self-learning robust (SLR) controller [35][36][37][38].…”

Section: Introductionmentioning

confidence: 99%

Robust adaptive backstepping control of H‐bridge inverter based on type‐2 fuzzy optimization of parameters

Azarinfar,

Khosravi,

Soroush

et al. 2024

IET Power Electronics

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A type‐2 fuzzy logic‐based adaptive backstepping control (T2FABSC) approach is designed for an H‐bridge inverter. This inverter has an LC filter to decrease the level of total harmonic distortion (THD) that can affect the efficiency of the system. Reduction of THD and stability insurance of the filter are challenging trade‐offs, tackled here by a controller design. The performance, however, is not suitable for actual applications under a wider range of disturbances, and the parameters need to be adjusted once more for more dependable operations. Backstepping control is given a Lyapunov definition‐based adaptive mechanism that can improve this scheme's stability and robustness in the face of numerous disturbances. Additionally, the system is viewed as a “Black box” without the need for a precise mathematical model, which might lead to a lighter computing burden and simpler implementation. Moreover, a fuzzy type‐2 structure is adopted that can optimize the gains of the adaptive Backstepping controller (ABSC) in challenging conditions. The antlion optimization algorithm is employed to optimize the parameters of the membership functions in the fuzzy system, hence improving the performance of the controller. In addition, compared with different optimization algorithms, it can more quickly and accurately locate the best solutions. Finally, the findings of both the simulations and the experimental outputs are examined, proving the T2FABSC's significant robustness and faster dynamics in a variety of challenging circumstances.

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“…The proposed technique has a beneficial role in various practical applications such as robotics [24,25], nonlinear systems with uncertainty [26,27], motors [28,29], and power electronics [30,31]. Backstepping control (BSC) method is capable of reaching desirable prospects and reaching better stability insurance on the operation.…”

Section: Introductionmentioning

confidence: 99%

“…The systematic recursive control Lyapunov function-based (CLF), and step-by-step, strategy ensures the asymptotic convergence in sub-systems with suitable real-time implementation. More importantly, the desirable elimination of mismatched and matched uncertainty have introduced BSC as a reliable technique [33,34]. Furthermore, the backstepping method used for power converters in adaptive and non-adaptive conditions to enhance their performance with more straightforward structure.…”

Section: Introductionmentioning

confidence: 99%

Design of a novel robust type‐2 fuzzy‐based adaptive backstepping controller optimized with antlion algorithm for buck converter

Khavari

Ghamari

Abdollahzadeh

et al. 2023

IET Control Theory & Appl

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A type‐2 fuzzy logic‐based adaptive backstepping control (T2F‐ABSC) approach is presented for a DC/DC Buck converter. Lyapunov‐based backstepping control (BSC), which can guarantee convergence along with asymptotic stability of the system. Also, the black‐box technique is applied for the proposed system, which does not require an accurate mathematical model resulting in a lower computational burden, easy implementation, and lower dependency on the states of the model. On the other hand, for wider ranges of disturbances, including parametric variations, load uncertainty, supply voltage variation, and noise, this approach shows an unsuitable practical application based on its fixed gain values; therefore, the control parameters need to be optimized again to provide ideal operations. Type‐2 fuzzy structure is adopted here to optimize the gains of the ABSM in challenging conditions. Type‐2 fuzzy (T2F) has higher efficiency and faster dynamics with more adaptability to the system. To enhance the performance of the T2F, antlion optimization (ALO) has been used in this structure. ALO is a modern nature‐inspired algorithm, and it has some advantages over other optimizing algorithms. Furthermore, it has ability to find optimal answers in a shorter time, more accurately in contrast to the other optimization algorithms and is used to tune the membership function parameters of the (T2F) under the diverse search spaces. To depict the strength of the designed work, fuzzy‐PID and backstepping schemes proposed to carry out an analysis with this work.

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An adaptive backstepping control to ensure the stability and robustness for boost power converter in DC microgrids

Cited by 18 publications

References 32 publications

Review of Modern Control Technologies for Voltage Regulation in DC/DC Converters of DC Microgrids

Review of Modern Control Technologies for Voltage Regulation in DC/DC Converters of DC Microgrids

Robust adaptive backstepping control of H‐bridge inverter based on type‐2 fuzzy optimization of parameters

Design of a novel robust type‐2 fuzzy‐based adaptive backstepping controller optimized with antlion algorithm for buck converter

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