Fuzzy sliding mode-based control for PMSG maximum wind energy capture with compensated pitch angle

Abstract

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Robust Control of a PMSG-Based Wind Turbine Generator Using Lyapunov Function

“…Linear controllers are designed under specific operating conditions and are influenced by large external perturbations and parameter uncertainties. Therefore, several nonlinear control techniques are proposed, including the intelligent fuzzy sliding-mode control [37], radial basis function network-based neural network control [38], and adaptive fuzzy control [39]. However, these artificial intelligence control methods require prior behavioral knowledge about the WTG system and extensive training data.…”

“…However, these artificial intelligence control methods require prior behavioral knowledge about the WTG system and extensive training data. Although the nonlinear controllers in [37][38][39][40] led to exponential convergence of the state trajectories, finite-time controller (FTC) architectures [41] can push the control system error trajectories to zero in a pre-defined time, thus resulting in fast convergence of system states, high control accuracy in the steady state, and excellent robustness against perturbations and uncertainties.…”

Wind Turbine Driving a PM Synchronous Generator Using Novel Recurrent Chebyshev Neural Network Control with the Ideal Learning Rate

“…Over the past decade, many different control approaches were used for generators and WT for energy generation [11][12][13][14][15]. In [11], a fuzzy logic control is adopted to control the power of the wind electrical conversion system transmitted to the grid and generator speed.…”

“…In [14], a sliding mode control (SMC) strategy associated with the field-oriented control of a dual stator induction generator (DSIG) based wind energy conversion systems was proposed to control the output power of a DSIG. In [15], a fuzzy logic sliding mode loss-minimization control is adopted to control the speed of the PM synchronous generator, and PI controller is adopted to control the WT pitch angle. However, most of these approaches require the time-consuming trial-and-error tuning procedure to achieve satisfactory performance; some of them can not achieve satisfactory performance; and some of them do not possess online learning ability and given the stability analysis.…”