Distributed Secondary Control Based on Dynamic Diffusion Algorithm for Current Sharing and Average Voltage Regulation in DC Microgrids

This paper introduces a distributed secondary control scheme for achieving current sharing and average voltage regulation objectives in a DC microgrid.The proposed scheme employs a dynamic diffusion algorithm(DDA)instead of the consensus algorithm to enable distributed communication among converters.To help understand DDA,the relation of DDA and other diffusion algorithms is discussed in detail and its superiority is shown by comparison with diffusion and consensus algorithms.Furthermore,considering the discrete nature and different sampling time of the digital controller and communication network,a z-domain model of the entire DC microgrid is established.The influence of communication and secondary control parameters on the system stability is investigated.Based on the established model,the tolerable communication rates are obtained.Real-time simulations conducted on the OPAL-RT platform validate the effectiveness of the proposed scheme,showcasing its advantages in terms of convergence speed and stability.

Lift enhancement of airfoil and tip flow control for wind turbine

Two techniques that improve the aerodynamic performance of wind turbine airfoils are described. The airfoil $809, designed specially for wind turbine blades, and the airfoil FX60-100, having a higher lift-drag ratio, are selected to verify the flow control techniques. The flow deflector, fixed at the leading edge, is employed to control the boundary layer separation on the airfoil at a high angle of attack. The multi-island genetic algorithm is used to optimize the parameters of the flow deflector. The results indicate that the flow deflector can suppress the flow separation, delay the stall, and enhance the lift. The characteristics of the blade tip vortex, the wake vortex, and the surface pressure distributions of the blades are analyzed. The vortex diffuser, set up at the blade tip, is employed to control the blade tip vortex. The results show that the vortex diffuser can increase the total pressure coefficient of the core of the vortex, decrease the strength of the blade tip vortex, lower the noise, and improve the efficiency of the blade.

Artificial neural-network-based visible light positioning algorithm with a diffuse optical channel

Visible light positioning becomes popular recently. However, its performance is degraded by the indoor diffuse optical channel. An artificial neural-network-based visible light positioning algorithm is proposed in this Letter, and a trained neural network is used to achieve positioning with a diffuse channel. Simulations are made to evaluate the proposed positioning algorithm. Results show that the average positioning error is reduced about 13 times, and the positioning time is reduced about two magnitudes. Moreover, the proposed algorithm is robust with a different field-of-view of the receiver and the refiectivity of the wall, which is suitable for various position- ing applications.

TSR: algorithm of image hole-filling based on three-step repairing

In order to solve the hole-filling mismatch problem in virtual view synthesis, a three-step repairing(TSR) algorithm was proposed. Firstly, the image with marked holes is decomposed by the non-subsampled shear wave transform(NSST), which will generate high-/low-frequency sub-images with different resolutions. Then the improved Criminisi algorithm was used to repair the texture information in the high-frequency sub-images, while the improved curvature driven diffusion(CDD) algorithm was used to repair the low-frequency sub-images with the image structure information. Finally, the repaired parts of high-frequency and low-frequency sub-images are synthesized to obtain the final image through inverse NSST. Experiments show that the peak signal-to-noise ratio(PSNR) of the TSR algorithm is improved by an average of 2-3 dB and 1-2 dB compared with the Criminisi algorithm and the nearest neighbor interpolation(NNI) algorithm, respectively.

A new physical unclonable function architecture

This paper describes a new silicon physical unclonable function （PUF） architecture that can be fabri- cated on a standard CMOS process. Our proposed architecture is built using process sensors, difference amplifier, comparator, voting mechanism and diffusion algorithm circuit. Multiple identical process sensors are fabricated on the same chip. Due to manufacturing process variations, each sensor produces slightly different physical charac- teristic values that can be compared in order to create a digital identification for the chip. The diffusion algorithm circuit ensures further that the PUF based on the proposed architecture is able to effectively identify a population of ICs. We also improve the stability of PUF design with respect to temporary environmental variations like temperature and supply voltage with the introduction of difference amplifier and voting mechanism. The PUF built on the proposed architecture is fabricated in 0.18 μm CMOS technology. Experimental results show that the PUF has a good output statistical characteristic of uniform distribution and a high stability of 98.1% with respect to temperature variation from -40 to 100 ℃, and supply voltage variation from 1.7 to 1.9 V.

Diffuse optical tomography in the human brain: A briefly review from the neurophysiology to its applications

The present work describes the use of noninvasive diffuse optical tomography(DOT)technology to measure hemodynamic changes,providing relevant information which helps to understand the basis of neurophysiology in the human brain.Advantages such as portability,direct measurements of hemoglobin state,temporal resolution,non-restricted movements as occurs in magnetic resonance imaging(MRI)devices mean that DOT technology can be used in research and clinical fields.In this review we covered the neurophysiology,physical principles underlying optical imaging during tissue-light interactions,and technology commonly used during the construction of a DOT device including the source-detector requirements to improve the image quality.DOT provides 3 D cerebral activation images due to complex mathematical models which describe the light propagation inside the tissue head.Moreover,we describe briefly the use of Bayesian methods for raw DOT data filtering as an alternative to linear filters widely used in signal processing,avoiding common problems such as the filter selection or a false interpretation of the results which is sometimes due to the interference of background physiological noise with neural activity.