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Abstract

The paper deals with the application of the extended Kalman filters in the control structure of a two-mass drive system. In the first step only linear extended Kalman filter was used for the estimation of mechanical state variables of the drive including load torque value. The estimation algorithm showed good robustness to mechanical parameters variations. For the system with some parameters changing in the wide range, simultaneous estimation of the state variables and chosen system parameters is required. For this reason the non-linear extended Kalman filter, which estimates simultaneously state variables and mechanical parameters of the two-mass drive system, was developed. Parameters of covariance matrices of used Kalman filters were set using the genetic algorithm. Both proposed estimators were investigated in simulation and experimental tests, in the open-loop operation and in the state-feedback control system of the two-mass system.
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Abstract

This work presents the co-simulation approach to the analysis of control systems containing detailed models of electromagnetic and electromechanical converters. In this method of analysis the attention is paid to the whole system and not only to its electromagnetic part. The latter is described by equations resulted from the two-dimensional finite element discretisation of the Maxwell equations, and is coupled weakly with the remaining part of the system. The simulation is carried out in Matlab/Simulink environment wherein the coupling is realised through the S-function. Example results regarding simulation of the operation of the control system of an electrical machine and the operation of a power electronic converter are presented and compared with available reference data.
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