1-3hit |
Jium-Ming LIN Hsiu-Ping WANG Ming-Chang LIN
In this paper, the Linear Exponential Quadratic Gaussian with Loop Transfer Recovery (LEQG/LTR) methodology is employed for the design of high performance induction motor servo systems. In addition, we design a speed sensorless induction motor vector controlled driver with both the extended Kalman filter and the LEQG/LTR algorithm. The experimental realization of an induction servo system is given. Compared with the traditional PI and LQG/LTR methods, it can be seen that the system output sensitivity for parameter variations and the rising time for larger command input of the proposed method can be significantly reduced.
Chien-Sheng CHEN Jium-Ming LIN Wen-Hsiung LIU Ching-Lung CHI
To achieve more accurate measurements of the mobile station (MS) location, it is possible to integrate many kinds of measurements. In this paper we proposed several simpler methods that utilized time of arrival (TOA) at three base stations (BSs) and the angle of arrival (AOA) information at the serving BS to give location estimation of the MS in non-line-of-sight (NLOS) environments. From the viewpoint of geometric approach, for each a TOA value measured at any BS, one can generate a circle. Rather than applying the nonlinear circular lines of position (LOP), the proposed methods are much easier by using linear LOP to determine the MS. Numerical results demonstrate that the calculation time of using linear LOP is much less than employing circular LOP. Although the location precision of using linear LOP is only reduced slightly. However, the proposed efficient methods by using linear LOP can still provide precise solution of MS location and reduce the computational effort greatly. In addition, the proposed methods with less effort can mitigate the NLOS effect, simply by applying the weighted sum of the intersections between different linear LOP and the AOA line, without requiring priori knowledge of NLOS error statistics. Simulation results show that the proposed methods can always yield superior performance in comparison with Taylor series algorithm (TSA) and the hybrid lines of position algorithm (HLOP).
Chien-Sheng CHEN Jium-Ming LIN Wen-Hsiung LIU Ching-Lung CHI
Intelligent transportation system (ITS) makes use of vehicle position to decrease the heavy traffic and improve service reliability of public transportation system. Many existing systems, such as global positioning system (GPS) and cellular communication systems, can be used to estimate vehicle location. The objective of wireless location is to determine the mobile station (MS) location in a wireless cellular communications system. The non-line-of-sight (NLOS) problem is the most crucial factor that it causes large measured error. In this paper, we present a novel positioning algorithm based on genetic algorithm (GA) to locate MS when three BSs are available for location purpose. Recently, GA are widely used as many various optimization problems. The proposed algorithm utilizes the intersections of three time of arrival (TOA) circles based on GA to estimate the MS location. The simulation results show that the proposed algorithms can really improve the location accuracy, even under severe NLOS conditions.