This paper presents an estimator-based speed sensorless field-oriented control (FOC) method for induction machines, where the state estimator is based on a self-contained, non-linear model. This model characterises both the electrical and the mechanical behaviours of the machine and describes them with seven state variables. The state variables are estimated from the measured stator currents and from the known stator voltages by using an estimator algorithm. An important aspect is that one of the state variables is the load torque and, hence, it is also estimated by the estimator. Using this feature, the applied estimator-based speed sensorless control algorithm may be operated adequately besides varying load torque. In this work, two different variants of the control algorithm are developed based on the extended and the unscented Kalman filters (EKF, UKF) as state estimators. The dynamic performance of these variants is tested and compared using experiments and simulations. Results show that the variants have comparable performance in general, but the UKF-based control provides better performance if a stochastically varying load disturbance is present.
This paper presents a new control algorithm development approach for induction machines by using model-based design and a systematically built model architecture implemented in MATLAB/Simulink. The model architecture follows a threelayer structure, and it is developed according to the principle of functional decomposition and the needs of reusability and expandability. The first model layer consists of elementary model and algorithm components, the second contains a machine simulation model and a field-oriented control (FOC) algorithm, built upon the first layer's components, and the third realises the executable models by connecting the models and algorithms defined in the second layer. Furthermore, rapid control prototyping (RCP) is discussed as an experimental validation method, and an experimental setup with RCP is also introduced. The application of the presented methods is demonstrated by simulations as well as by experiments, and by using a control algorithm based on FOC as an example.
KeywordsInduction machine · Control algorithm development · Field-oriented control (FOC) · Model-based design (MBD) · Modular architecture · Rapid control prototyping (RCP) · MATLAB/Simulink Abbreviations DRFOC Direct rotor field-oriented control DSC Direct self-control DTC Direct torque control ECU Electronic control unit FOC Field-oriented control HIL Hardware-in-the-loop MBD Model-based design NIC Network interface control PMSM Permanent magnet synchronous machine PWM Pulse width modulation RCP Rapid control prototyping SRTT Simulink Real-Time target TI Texas instruments UI User interface List of symbols i ds d-Axis stator current (A) T l Load torque (Nm) p Number of pole pairs J Rotor inertia (kg m 2 ) D Viscous friction coefficient (Nm s/rad) T 0 Static friction (Nm)
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