Adaptive Backstepping Fuzzy Logic Controller for the PV battery system

Ambikapathy, A.; Govindharaj, Arunprasad; Dixit, Prakhar; Yadav, Shreya; Thirunavukkarasu, Ezhilan; Singh, Sudhakar; Tulsiram, Shaky Neetu; Arun, S

doi:10.1109/icacite53722.2022.9823828

Cited by 1 publication

(1 citation statement)

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“…This adaptive technique has achieved significant outcomes applied to other control methods. One can consider Sliding-based ABSC [40,41], Fuzzy-based ABSC [42], H ∞ ABSC [43], and Feedback adaptive strategy in refs. [44,45].…”

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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