Abstract
In this paper,the rotor speed and the position of the SSP propulsion motor are estimated for building sensorless vector control system with speed and current double closed loops based on square root center difference Kalman filter (SR-CDKF) algorithm. This method makes use of the QR decomposition linear algebra techniques and so on, and it updates the matrix square-root of the state covariance by the Cholesky factor updating. This method can not only get the more steady results but also improve the estimation accuracy of the SSP podded propulsion system. Simulation result shows that the improved CDKF algorithm is not only more accurate but also has higher rate of convergence compared with CDKF speed controller.
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