This paper presents an output power smoothing method by a simple coordinated control of DC-link voltage and pitch angle of a wind energy conversion system (WECS) with a permanent magnet synchronous generator (PMSG). The WECS adopts an AC-DC-AC converter system with voltage-source converters (VSC). The DC-link voltage command is determined according to output power fluctuations of the PMSG. The output power fluctuationsin low-and high-frequency domains are smoothed by the pitch angle control of the WECS, and the DClink voltage control, respectively. By using the proposed method, the wind turbine blade stress is mitigated as the pitch action in high-frequency domain is reduced. In addition, the DC-link capacitor size is reduced without the charge/discharge action in lowfrequency domain. A chopper circuit is used in the DC-link circuit for stable operation of the WECS under-line fault. Effectiveness of the proposed method is verified by the numerical simulations.Index Terms-Permanent magnet synchronous generator, pitch control, power smoothing, wind energy conversion system.

This sequel is concerned with the analysis of projective lag synchronization of Riemann–Liouville sense fractional order memristive BAM neural networks (FOMBNNs) with mixed time delays via hybrid controller. Firstly, a new type of hybrid control scheme, which is the combination of open loop control and adaptive state feedback control is designed to guarantee the global projective lag synchronization of the addressed FOMBNNs model. Secondly, by using a Lyapunov–Krasovskii functional and Barbalet’s lemma, a new brand of sufficient criterion is proposed to ensure the projective lag synchronization of the FOMBNNs model considered. Moreover, as special cases by using a hybrid control scheme, some sufficient conditions are derived to ensure the global projective synchronization, global complete synchronization and global anti-synchronization for the FOMBNNs model considered. Finally, numerical simulations are provided to check the accuracy and validity of our obtained synchronization results.

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Fractional order quaternion‐valued neural networks are a type of fractional order neural networks for which neuron state, synaptic connection strengths, and neuron activation functions are quaternion. This paper is dealing with the Mittag‐Leffler stability and adaptive impulsive synchronization of fractional order neural networks in quaternion field. The fractional order quaternion‐valued neural networks are separated into four real‐valued systems forming an equivalent four real‐valued fractional order neural networks, which decreases the computational complexity by avoiding the noncommutativity of quaternion multiplication. Via some fractional inequality techniques and suitable Lyapunov functional, a brand new criterion is proposed first to ensure the Mittag‐Leffler stability for the addressed neural networks. Besides, the combination of quaternion‐valued adaptive and impulsive control is intended to realize the asymptotically synchronization between two fractional order quaternion‐valued neural networks. Ultimately, two numerical simulations are provided to check the accuracy and validity of our obtained theoretical results.