Nonlinear model predictive control applied to a DFIG-based wind turbine with a Shunt APF

Kachani, Abderrahmane El; Chakir, E.; Laachir, Anass Ait; Jarou, Tarik; Hadjoudja, Abdelkader

doi:10.1109/irsec.2016.7983962

Cited by 5 publications

(1 citation statement)

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“…However, it increases the computational cost, which is critical in real-time systems with a low-cost DSP, especially when it uses high-frequency rates, which is DFIG's case. Therefore, there are some works with non-linear models but limited to simulations [20], [25], [26]. An interesting alternative is the adaptive robust control [27], due to its capability to deal with structured and unstructured uncertainties, especially to deal with fault operation conditions produced by voltage sags.…”

Section: Introductionmentioning

confidence: 99%

Predictive Incremental Vector Control for DFIG With Weighted-Dynamic Objective Constraint-Handling Method-PSO Weighting Matrices Design

et al. 2020

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paper proposes a Particle Swarm Optimization (PSO) based method, the Weighted-Dynamic-Objective Constraint-Handling PSO Method (WDOCHM-PSO). This was used to design the weighting matrices of an incremental Model-Based Predictive Controller (MBPC) for a Doubly Fed Induction Generator (DFIG) applied in a small-scale wind energy system. In contrast to the original PSO, the proposed method has an inner mechanism for dealing with constraints and an adaptive search factor. Additionally, the proposed incremental MPBC implementation does not need the flux information, since the intrinsic integral action rejects the constant flux disturbance. Finally, experimental results show that the proposed controller with the new constraint handling design method is nearly two times faster (In terms of settling time) than other formulations reported in the literature.

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Section: Introductionmentioning

confidence: 99%