Computer Network Time Synchronization using a Low Cost GPS Engine

Accurate and reliable time is necessary for financial and legal transactions, transportation, distribution systems, and many other applications. Time synchronization protocols such as NTP (the Network Time Protocol) have kept clocks of such applications synchronized to each other for many years. Nowadays there are many commercial GPS based NTP time server products at the market but they almost have a high price. In this paper we are going to use a low cost GPS engine to build a time server to provide time synchronization with accuracy of a few milliseconds. This time server is relatively very cheap and it can be used in almost all typical applications. We also proposed a software based NTP time server implemented in MATLAB as well

A New Strategy for Short-Term Power-Curve Prediction of Wind Turbine Based on PSO-LS-WSVM

Wind turbines are very important and strategic instruments in energy markets. Wind power production is unreliable. Wind power is weather dependent and the extreme wind speed changes make difficult to control of grid voltage and reactive power. Based on these reasons, Wind Power Prediction (WPP) is important for real applications. In this paper, a new short-term WPP method based on Support Vector Machine (SVM) is proposed. In contrast to physical approaches based on very complex differential equations, the proposed method is based on data history. Firstly, data preprocessing and normalization is done. Secondly, formulate the prediction as a regression problem. Thirdly, the prediction model is constructed using the Particle Swarm Optimization (PSO) and Least Square Support Vector Machine (LSSVM). In this paper, instead of using the conventional kernels, such as linear kernel, Polynomial and Radial basis function (RBF), the Wavelet (W) transform is used. The PSO-LS-WSVM accuracy has been tested with industrial wind energy data. This method has been compared with other methods and the experimental results based on practical data illustrate that PSO-LS-WSVM proposed method has better responses than other methods. Statistical results indicate that the predicting error of PSO-LS-WSVM is 2.98% for one look-ahead hour

Real Time Pseudo-Range Correction Predicting by a Hybrid GASVM model in order to Improve RTDGPS Accuracy

Differential base station sometimes is not capable of sending correction information for minutes, due to radio interference or loss of signals. To overcome the degradation caused by the loss of Differential Global Positioning System (DGPS) Pseudo-Range Correction (PRC), predictions of PRC is possible. In this paper, the Support Vector Machine (SVM) and Genetic Algorithms (GAs) will be incorporated for predicting DGPS PRC information. The Genetic Algorithm is employed to feature subset selection. Online training for real-time prediction of the PRC enhances the continuity of service on the differential correction signals and therefore improves the positioning accuracy in Real Time DGPS. Given a set of data received from low cost GPS module, the GASVM can predict the PRC precisely when the PRC signal is lost for a short period of time. This method which is introduced for the first time for prediction of PRC is compared to other recently published methods. The experiments show that the total RMS prediction error of GASVM is less than 0.06m for on step and 0.16m for 10 second ahead case

Design of a Resonant Suspended Gate MOSFET with Retrograde Channel Doping

High Q frequency reference devices are essential components in many Integrated circuits. This paper will focus on the Resonant Suspended Gate (RSG) MOSFET. The gate in this structure has been designed to resonate at 38.4MHz. The MOSFET in this device has a retrograde channel to achieve high output current. For this purpose, abrupt retrograde channel and Gaussian retrograde channels have been investigated