Design of a robust adaptive self-tuning regulator controller on single-phase full-bridge grid-connected inverter

Ghamari, Seyyed Morteza; Gholizade‐Narm, Hossein; Khavari, Fatemeh

doi:10.1007/s40435-022-00963-z

Cited by 9 publications

(5 citation statements)

References 32 publications

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“…The primary concept of this process is based on ants' behaviors motions in the search space, while antlion predicts their next move to hunt them [36]. It should be mentioned that the movements of ants are not fixed; thus, their random behavior can be modeled by Equation (5).…”

Section: Optimizer Algorithm Of Antlionmentioning

confidence: 99%

“…The primary aim of utilizing power converters is regulating the output voltage and ensuring a robust dynamic performance. The objective of designing a feedback loop control is for the stability insurance of the system and appropriate regulation within a predetermined range of operating conditions [4,5]. On the other hand, this converter's system consisted of a zero in the right half-plane, which provides a challenging condition to design flexible and well-behaved controllers.…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand, the controllers stated in these papers are single-loop methods with sufficient robustness; also, they suffer from a lack of protection against short circuit problems leading to more requirements for additional circuity. In addition, based on the research done by [5,27,28], the primary issues considering single-loop controllers for power converters are as follows: (i) Poor operation in the presence of constant variations over the supply voltage, (ii) lack of current feedback loop leads to high risk of instability, (iii) No inherent protection against short circuits, (vi) high transients in their operations, (v) supply voltage alterations can highly impact the dynamics and gains of the system, and (vi) vulnerability to a wide range of load variations and uncertainty. In this work, all the mentioned issue have been tried to be addressed.…”

Section: Introductionmentioning

confidence: 99%

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Design of a novel robust adaptive cascade controller for DC‐DC buck‐boost converter optimized with neural network and fractional‐order PID strategies

Ghamari

Jouybari

Mollaee

et al. 2023

The Journal of Engineering

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A cascade technique with two control loops is designed for a DC\DC Buck-Boost converter that is a right half-plane zero (RHPZ) structure called a non-minimum phase system. This concept presents several challenging constraints for designing well-behaved control techniques. Cascade controllers can provide various benefits compared with single loop controllers such as higher safety, higher robustness, and higher stability. This strategy assumes the system as a black-box structure without the need for a mathematical model of the system. This benefit can decrease the computational burden and provides faster dynamics along with ease of implementation. This technique consisted of an outer Fractional-order PID voltage controller tuned with the Antlion Optimizer (ALO) algorithm, which provides a reference current for the inner control loop of the Neural Network-based LQR (NN-LQR) controller. The basic principle in cascade controllers is a more rapid performance of the inner loop that has been satisfied with the NN-LQR strategy, which optimizes and tunes the gains of the LQR controller and shows faster dynamics and higher robustness. It should be mentioned that the number of neurons is limited to 2 and 4 in each layer to decrease the computational burden with lower complexity. Also, the ALO algorithm is a modern nature-inspired algorithm used to tune the PID gains with better results under-constrained problems with diverse search spaces. Considering the negative impacts of various disturbances on a power converter, a Fractional-order-based PID (FO-PID) control technique is a proper alternative since it shows higher robustness in load uncertainties along with better dynamical responses based on its extra degree of freedom. Moreover, to evaluate the superiority of this controller, two other controllers are designed using the PSO algorithm for PID and FO-PID controllers. Finally, the presented cascade controller has been tested in various working conditions through simulation and experiment results.

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Section: Optimizer Algorithm Of Antlionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Design of a novel robust adaptive cascade controller for DC‐DC buck‐boost converter optimized with neural network and fractional‐order PID strategies

Ghamari

Jouybari

Mollaee

et al. 2023

The Journal of Engineering

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“…To reduce the THD level, inductive filters (L) or capacitive filters (C) are suggested, including, LC, L, LLCL, and LCL. Papers [3][4][5] reported that the characteristics of LC filters make them appropriate options for stand-alone structures (load connected). However, they also pointed out that under high-frequency switching conditions, this topology exhibits a discontinuous behaviour, and that in real-time use, some fractionality and hitherto observed non-linearity also arise [6].…”

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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“…These challenges are covered in refs. [15][16][17] using a robust identification procedure in the controller that does not require a mathematical model of system using Backbox strategy. Meanwhile, these flexible schemes highly rely on the identification process leading to the lack of reliability along with higher instability risk.…”

Section: Introductionmentioning

confidence: 99%

Adaptive backstepping controller design for DC/DC buck converter optimised by grey wolf algorithm

Ghamari

Khavari

Mollaee

2023

IET Energy Syst Integration

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A Lypunov‐based Adaptive Backstepping Control (ABSC) approach is designed for a power Buck converter. This strategy is an advanced version of the Backstepping method utilising Lyapunov stability function to reach a higher stability and a better disturbance rejection behaviour in the practical applications. In addition, to reduce the computational burden and increase ease of implantation, Black‐box technique is considered assuming no accurate mathematical model for the system. Nonetheless, in real‐time environments, disturbances with wider ranges including: supply voltage variation, parametric variation, and noise can negatively impact the operation of this method. To compensate for this problem, the gains of the controller should be tuned again for better adaptability with the working condition. Therefore, to satisfy this need and enhance the controller's performance, a metaheuristic algorithm is applied in the control scheme called Grey Wolf Optimisation (GWO) algorithm. GWO is a well‐behaved nature‐inspired algorithm with faster decision‐making dynamics along with more accuracy over different optimisation algorithms. To better elaborate the merits of this approach, conventional BSM and PSO‐based PID schemes are also designed and tested in different situations.

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Design of a robust adaptive self-tuning regulator controller on single-phase full-bridge grid-connected inverter

Cited by 9 publications

References 32 publications

Design of a novel robust adaptive cascade controller for DC‐DC buck‐boost converter optimized with neural network and fractional‐order PID strategies

Design of a novel robust adaptive cascade controller for DC‐DC buck‐boost converter optimized with neural network and fractional‐order PID strategies

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

Adaptive backstepping controller design for DC/DC buck converter optimised by grey wolf algorithm

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