Title :
FPGA implementation of marginalized particle filter for sensorless control of PMSM drives
Author :
Smidl, Vaclav ; Nedved, Robert ; Kosan, Tomas ; Peroutka, Zdenek
Author_Institution :
Regional Innovation Centre for Electr. Eng., Univ. of West Bohemia, Pilsen, Czech Republic
Abstract :
Marginalized particle filter is a stochastic filter combining Kalman filters with particle filters. It decomposes the model into linear and nonlinear part and applies the Kalman filter for the former and the particle filter for the latter. In effect, this allows to represent accurately the inherent non-Gaussianity and nonlinearity of the model. This allows estimation of the rotor position of the PMSM drive in the full speed range, including the standstill. The main disadvantage is its high computational cost. In this paper, we present an implementation of the marginalized particle filter in the field programmable logic array (FPGA). The parallel nature of the MPF algorithm allows to use pipelining which yields speedup in the order of magnitude in comparison to the DSP implementation. The sensorless control of the drive is implemented on a board with both DSP and FPGA, where the drive control runs on the DSP and the MPF estimator in the FPGA. Execution time of the estimator is thus negligible in the execution time of the sensorless control. Performance of the resulting sensorless control algorithm is evaluated on a developed drive prototype of rated power of 10.7kW.
Keywords :
Kalman filters; digital signal processing chips; field programmable gate arrays; particle filtering (numerical methods); permanent magnet motors; rotors; sensorless machine control; stochastic processes; synchronous motor drives; DSP implementation; FPGA implementation; Kalman filter; MPF estimator; PMSM drive; drive control; field programmable logic array; marginalized particle filter; non-Gaussianity; pipelining; rotor position estimation; sensorless control; sensorless control algorithm; stochastic filter; Digital signal processing; Field programmable gate arrays; Kalman filters; Mathematical model; Pipelines; Rotors; Sensorless control;
Conference_Titel :
Industrial Electronics Society, IECON 2013 - 39th Annual Conference of the IEEE
Conference_Location :
Vienna
DOI :
10.1109/IECON.2013.6700510