Robust nonlinear MPPT controller for PV energy systems using PSO-based integral backstepping and artificial neural network techniques

A PV system is subject to random variations in environmental conditions, and continuous tracking of the maximum power point is an indispensable step to improve the PV operational efficiency. Numerous techniques of maximum power point tracking have been reported in the literature. However, these tech...

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Bibliographic Details
Published in:	International journal of dynamics and control Vol. 12; no. 5; pp. 1598 - 1615
Main Authors:	Harrison, Ambe, Dieu Nguimfack-Ndongmo, Jean de, Alombah, Njimboh Henry, Aloyem Kazé, Claude Vidal, Kuate-Fochie, René, Asoh, Derek Ajesam, Nfah, Eustace Mbaka
Format:	Journal Article
Language:	English
Published:	Berlin/Heidelberg Springer Berlin Heidelberg 01-05-2024 Springer Nature B.V
Subjects:	Artificial neural networks Closed loops Complexity Control Control and Systems Theory Control systems Controllers Dynamical Systems Engineering Feedback control Mathematical models Maximum power tracking Neural networks Nonlinear control Nonlinear systems Particle swarm optimization Robust control Sliding mode control Vibration Integral backstepping ANN PV systems MPPT Particle swarm optimization
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