| Summary: | This 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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