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This paper proposes a novel paradigm for facial privacy protection that unifies multiple characteristics including anonymity, diversity, reversibility and security within a single lightweight framework. We name it PRO-Face S, short for Privacy-preserving Reversible Obfuscation of Face images via Secure flow-based model. In the framework, an Invertible Neural Network (INN) is utilized to process the input image along with its pre-obfuscated form, and generate the privacy protected image that visually approximates to the pre-obfuscated one, thus ensuring privacy. The pre-obfuscation applied can be in diversified form with different strengths and styles specified by users. Along protection, a secret key is injected into the network such that the original image can only be recovered from the protection image via the same model given the correct key provided. Two modes of image recovery are devised to deal with malicious recovery attempts in different scenarios. Finally, extensive experiments conducted on three public image datasets demonstrate the superiority of the proposed framework over multiple state-of-the-art approaches.

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To eliminate the harmonics caused by nonlinear loads, repetitive controllers are widely applied as current controllers for active power filters (APF). In practice, a variation in grid frequency leads to the appearance of a fractional-order delay filter. As a result, the resonant frequency of the repetitive controller will deviate from the fundamental frequency and the controller cannot compensate for harmonics accurately. To solve this problem, an improved frequency-adaptive repetitive controller based on virtual variable sampling (IMFA-VVS-RC) for APF is proposed in this paper. To enhance the system stability margin, the proposed RC introduces an infinite impulse response (IIR) low-pass filter. The proposed RC has a high stability margin at high frequencies due to the low gain of the IIR low-pass filter in the region above the cutoff frequency. In this way, the influence of model uncertainty and parameter uncertainty on system stability are reduced at high frequencies. At the same time, compared with the conventional repetitive controller (CRC), the proposed RC for APF has a better harmonic suppression ability when the frequency varies. Experiments have verified the effectiveness of the scheme adopted for APF.