Chattering Free Adaptive Sliding Mode Controller for Photovoltaic Panels with Maximum Power Point Tracking

Hina Gohar Ali, Ramon Vilanova i Arbós

Research output: Contribution to journalArticleResearchpeer-review

9 Citations (Scopus)

Abstract

Photovoltaic system is utilized to generate energy that relies upon the ecological conditions, for example, temperature, irradiance, and the load associated with it. Considering the non-linear component of photovoltaic (PV) array and the issue of low effectiveness because of the variable natural conditions, the Maximum Power Point Tracking (MPPT) method is required to extract the maximum power from the PV system. The adopted control is executed utilizing an Adaptive Sliding Mode Controller (ASMC) and the enhancement is actualized utilizing an Improved Pattern Search Method (IPSM). This work employs IPSM based optimization approach in order to command the underlying ASMC controller. The upper level decision determines the sliding surface for the adaptive controller. As a non-linear strategy, the stability of the adaptive controller is guaranteed by conducting a Liapunov analysis. On the practical side, MATLAB/Simulink is used as simulator for the controller implementation and coupling with PSIM in order to connect it with the PV system object of control. The simulation results validate that the proposed controller effectively improves the voltage tracking, system power with reduced chattering effect and steady-state error. The performance of the proposed control architectures is validated by comparing the proposals with that of the well-known and widely used Proportional Integral Derivative (PID) controller. That operated as a lower level controller for a Perturb & Observe (P&O) and Particle Swarm Optimization (PSO).
Original languageEnglish
JournalEnergies
Volume13
Issue number21
DOIs
Publication statusPublished - 2020

Keywords

  • Photovoltaic (PV)
  • Maximum power point tracking (MPPT)
  • Adaptive sliding mode controller (ASMC)
  • Improved pattern search method (IPSM)
  • Particle swarm optimization (PSO)

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