The main idea presented in this paper is to use interval analysis technique on state estimation of nonlinear dynamic system, in this concrete case the PMSM (Permanent Magnet Synchronous Machine). PMSM drives offers in comparison to other drives several advantages but it is necessary to have knowledge of actual rotor position and actual speed of rotation for precise control. Measurement of these state variables is technically or financially unnecessarily consumptive. These data are usually obtained by state observers, in most cases by extended Kalman filter or his modifications. Unfortunately, in many cases this is insufficient. That is why other methods of state estimation are being researched. One of these methods is interval analysis in which results are not points, but intervals. Advantage of this is that these intervals are guaranteed.
This paper deals with model predictive control (MPC) algorithm applied to speed control of permanent magnet synchronous machine (PMSM). Key aspects related to optimization of linear model PMSM are: the use of Field Oriented Control scheme (FOC) to employ linearized model of PMSM in dq-coordinates and elimination of cascade control loop. Speed and current controllers are combined together. In this way, the controller enforces both the current and the voltage limits. The simulation results are carried out in Matlab/Simulink environment with use of Multi-parametric toolbox.I.
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