A rapid flood inundation model for hazard mapping based on least squares support vector machine regression

2019 ◽  
Vol 12 (S1) ◽  
Author(s):  
María Bermúdez ◽  
Luis Cea ◽  
Jerónimo Puertas
Keyword(s):  
Support Vector Machine ◽  
Least Squares ◽  
Support Vector ◽  
Hazard Mapping ◽  
Flood Inundation ◽  
Support Vector Machine Regression ◽  
Inundation Model

scholarly journals PERMANENT SYNCHRON MAGNET MOTOR SPEED OBSERVER BASED ON LEAST SQUARES SUPPORT VECTOR MACHINE REGRESSION

2020 ◽  
Vol 13 (2) ◽  
pp. 17-24
Author(s):  
Muldi Yuhendri ◽  
Hambali Hambali ◽  
Mukhlidi Muskhir
Keyword(s):  
Support Vector Machine ◽  
Least Squares ◽  
Permanent Magnet ◽  
Permanent Magnet Synchronous Motor ◽  
Synchronous Motor ◽  
Support Vector ◽  
Motor Speed ◽  
Support Vector Machine Regression ◽  
Adaptation Mechanism ◽  
Speed Sensor

Motor speed control requires motor speed data as feedback from control actions. Motor speed data is usually obtained from the speed sensor. In this paper, the motor speed observer for permanent magnet synchronous motor is proposed to obtain motor speed data based on motor back emf voltage making it more economical without a speed sensor. The Speed observer is designed based on the Model Reference Adapative System (MRAS) with using Least Squares Support Vector Machine Regression (LSSVMR) algorithm for adaptation mechanism tools. The proposed speed observer is tested with varying motor speeds. The test results show that the MRAS-based motor speed observer using LSSVMR has successfully estimated the rotation speed of the permanent magnet synchronous motor based on the back emf motor voltage. It can be seen from the maximum error of  the motor speed, ie only 3.7 rpm at transient conditions and close to zero at steady state

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