Estimating significant wave height from SAR imagery based on an SVM regression model

A new method for estimating significant wave height（SWH） from advanced synthetic aperture radar（ASAR） wave mode data based on a support vector machine（SVM） regression model is presented. The model is established based on a nonlinear relationship between σ0, the variance of the normalized SAR image, SAR image spectrum spectral decomposition parameters and ocean wave SWH. The feature parameters of the SAR images are the input parameters of the SVM regression model, and the SWH provided by the European Centre for Medium-range Weather Forecasts（ECMWF） is the output parameter. On the basis of ASAR matching data set, a particle swarm optimization（PSO） algorithm is used to optimize the input kernel parameters of the SVM regression model and to establish the SVM model. The SWH estimation results yielded by this model are compared with the ECMWF reanalysis data and the buoy data. The RMSE values of the SWH are 0.34 and 0.48 m, and the correlation coefficient is 0.94 and 0.81, respectively. The results show that the SVM regression model is an effective method for estimating the SWH from the SAR data. The advantage of this model is that SAR data may serve as an independent data source for retrieving the SWH, which can avoid the complicated solution process associated with wave spectra.

Numerical simulation of a two-dimensional flapping wing in advanced mode

A two-dimensional model is built to describe the translation and the rotation of the hovering flapping movement. The equations of motion are derived for insect＇s flapping movement, and the model is implemented by the computational fluid dynamics（CFD） software FLUENT and it？s user defined function（UDF）. It is shown that the lift coefficient changes slowly in the intermediate stage, there are two areas in which the lift coefficient changes dramatically, and the drag coefficient behaves quite differently when flapping up and down. The vortex distribution, the pressure distribution, and the velocity vector distribution in the advanced mode at different times follow quite various rules.

Improved Synergetic Current Control for Grid-connected Microgrids and Distributed Generation Systems

This paper presents the development of improved synergetic current control for the injected current of an inverter in the grid-connected microgrid and the distributed generation system(DGS). This paper introduces new formulas of the macro-variable functions for integral synergetic control(SC)and integral fast terminal SC, which both have an integral term to guarantee zero steady-state error. The proposed integral SC and integral fast terminal SC achieve a seamless performance such as the fast convergence, minimal overshoot, zero steady-state error, and chattering-free operation. To demonstrate the meritorious performance of the proposed scheme for injected current control, it is compared with the performance of a proportional-integral(PI) controller and advanced exponential sliding mode control(SMC). Finally, the practicality of the proposed scheme is justified by experimental results obtained through rapid control prototyping(RCP) using the dSPACESCALEXIO platform.