MPPT Performance and Power Quality Improvement by Using Fractional-Order Adaptive Backstepping Control of a DFIG-Based Wind Turbine with Disturbance and Uncertain Parameters

Kasbi, Abdellatif; Rahali, Abderrafii

doi:10.1007/s13369-022-07474-1

Cited by 11 publications

(3 citation statements)

References 42 publications

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“…The following equation gives the Lyapunov function connected to the stator's active and reactive power errors (eq (36) ) [ 68 ]:

…”

Section: Rotor Side Converter Controlmentioning

confidence: 99%

Nonlinear robust sliding mode - Backstepping hybrid control for WECS -theoretical design and experimental evaluation

Echiheb,

Elkafazi,

Bossoufi

et al. 2024

Heliyon

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“…The following equation gives the Lyapunov function connected to the stator's active and reactive power errors (eq (36) ) [ 68 ]:

…”

Section: Rotor Side Converter Controlmentioning

confidence: 99%

Nonlinear robust sliding mode - Backstepping hybrid control for WECS -theoretical design and experimental evaluation

Echiheb,

Elkafazi,

Bossoufi

et al. 2024

Heliyon

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“…The traditional linear control strategy used to realize the stator-rotor coordinated MPPT control, for ex- ample, air-gap flux orientation control [7], stator flux orientation control [8], model predictive control [9], single-loop finite control set model predictive control [10], single-loop feedback linearization control [11]. However, the conventional linear control strategy exhibits certain inherent limitations that cannot be disregarded, including reliance on system models, inadequate model accuracy, suboptimal efficiency, and unsatisfactory transient performance [12,13]. Therefore, nonlinear control strategies are used in this system.…”

Section: Introductionmentioning

confidence: 99%

Single-Loop Robust Decoupling Control Base on Perturbation Estimation for DC-Based DFIG

Sun,

Yang,

Zhang

2024

IEEE Access

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This paper presents a perturbation observer based single-loop robust decoupling control scheme (RDC-PO) for DC-based DFIG with dual voltage source converters to enhance maximum power point tracking (MPPT) and improve fault-ride-through (FRT) capability. The unknown nonlinear effects caused by aerodynamic and modeling uncertainties are aggregated into a perturbation term, which is estimated by a sliding-mode perturbation observer. Then, a single-loop linear feedback controller with no intermediate link is designed to quickly compensate disturbance estimation in real time. Furthermore, the control algorithm does not necessitate a precise DFIG model. Additionally, the incorporation of nonlinear robust control compensates for the inherent limitations of linear control, thereby endowing the proposed control algorithm with the advantages of facile implementation akin to traditional linear control and global consistency characteristic of nonlinear robust control. Simulation results show that RDC-PO has superior transient and steady-state performance compared with double-loop feedback controller (DFC) and single-loop feedback control (SFC) in MPPT and FRT. Finally, Experiment verifies the practical operability of the proposed strategy. INDEX TERMS DC-based DFIG, perturbation observer, single-loop controller, MPPT, FRT

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“…More importantly, the desirable elimination of mismatched and matched uncertainty have introduced BSC as a reliable technique using non-linear benefits of Lyapunov function. More interestingly, this method is utilised for power Converters in both adaptive and non-adaptive conditions enhancing the performance of the control method with more straightforward mechanism [37][38][39]. This adaptive technique has achieved significant outcomes applied to other control methods.…”

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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MPPT Performance and Power Quality Improvement by Using Fractional-Order Adaptive Backstepping Control of a DFIG-Based Wind Turbine with Disturbance and Uncertain Parameters

Cited by 11 publications

References 42 publications

Nonlinear robust sliding mode - Backstepping hybrid control for WECS -theoretical design and experimental evaluation

Nonlinear robust sliding mode - Backstepping hybrid control for WECS -theoretical design and experimental evaluation

Single-Loop Robust Decoupling Control Base on Perturbation Estimation for DC-Based DFIG

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

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