Optimal BISMC Controller with Evolutionary Algorithm for MPPT based Photovoltaic System

2019 International Conference on Intelligent Systems and Advanced Computing Sciences (ISACS) Pub Date : 2019-12-01 DOI:10.1109/ISACS48493.2019.9068913

F. Lamzouri, El-mahjoub Boufounas, M. Hanine, A. El Amrani

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Abstract

The present paper considers an optimal robust backstepping integral sliding mode controller using particle swarm optimization (PSO-BISMC) based maximum power point tracking (MPPT) of a photovoltaic (PV) system in variable atmospheric conditions. The PSO-BISMC controller, proposed as an original approach, combines the features of both standard sliding mode control (SMC) and backstepping approaches. Moreover, the integral action is introduced in the tracking error term to improve the BSMC controller performance. On the other hand, the PSO method is applied to optimize the BISMC controller parameters. The controlled PV system stability is demonstrated using the lyapunov function. Furthermore, simulation studies of the proposed PSO-BISMC are investigated and compared with the BISMC controller as well as to the BSMC controller. Simulation results prove that the proposed approach show more robustness against atmospheric conditions variation with fast transition response and best tracking performance compared to other controllers (i.e. BISMC and BSMC).

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基于 MPPT 的光伏系统的最优 BISMC 控制器与进化算法

本文研究了基于粒子群优化（PSO-BISMC）的光伏（PV）系统在多变大气条件下最大功率点跟踪（MPPT）的最优鲁棒反步进积分滑模控制器。作为一种原创方法提出的 PSO-BISMC 控制器结合了标准滑模控制 (SMC) 和反步进方法的特点。此外，在跟踪误差项中引入了积分作用，以提高 BSMC 控制器的性能。另一方面，应用 PSO 方法优化 BISMC 控制器参数。利用 lyapunov 函数证明了受控光伏系统的稳定性。此外，还对所提出的 PSO-BISMC 进行了仿真研究，并与 BISMC 控制器和 BSMC 控制器进行了比较。仿真结果证明，与其他控制器（即 BISMC 和 BSMC）相比，所提出的方法对大气条件变化具有更强的鲁棒性、快速的过渡响应和最佳的跟踪性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2019 International Conference on Intelligent Systems and Advanced Computing Sciences (ISACS)

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