Title: Intelligent proportional-integral sliding mode control of wind turbine systems based particle swarm optimisation

Authors: Salma Aboulem; El-mahjoub Boufounas; Ismail Boumhidi

Addresses: Department of Physics, LESSI Laboratory, Faculty of Sciences Dhar El Mehraz, University Sidi Mohamed Ben Abdellah, B.P. 1796, 30000 FES-Atlas, Morocco ' Department of Physics, LPSMS Laboratory, Faculty of Sciences and Technology, Moulay Ismail University, B.P. 509, Boutalamine, Errachidia, Morocco ' Department of Physics, LESSI Laboratory, Faculty of Sciences Dhar El Mehraz, University Sidi Mohamed Ben Abdellah, B.P. 1796, 30000 FES-Atlas, Morocco

Abstract: This paper presents a robust intelligent proportional-integral sliding mode controller for a variable speed wind turbine (VSWT). The main objective of the controller is to optimise the energy captured from the wind, and minimise the mechanical stress in the system. In order to guarantee the wind power capture optimisation without any chattering problems, this study propose to combine the sliding mode control (SMC), proportional integral (PI) control and particle swarm optimisation (PSO) algorithm. The PSO technique with efficient global search is used to optimise the PI and SMC parameters simultaneously to control the system trajectories to a sliding manifold that determines the system performance. The stability of the system using this controller is shown by the Lyapunov theory. The simulation results of the proposed PSO-PI based SMC (PSO-PISMC) method are compared with the PSO-I based SMC (PSO-ISMC) and the conventional PSO based SMC (PSO-SMC). The comparison results reveal that the proposed controller is more effective in reducing the tracking error and chattering. In addition, the controller shows more robustness against uncertainties and faster transient response of the system with reduced steady state error.

Keywords: sliding mode control; PI sliding surface; particle swarm optimisation; variable-speed wind turbine.

DOI: 10.1504/IJAAC.2019.098585

International Journal of Automation and Control, 2019 Vol.13 No.3, pp.347 - 373

Accepted: 25 Nov 2017
Published online: 28 Mar 2019 *

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