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In this work, a Sensorless hybrid control system is proposed for PMSMs requiring only knowledge of flux linkage. The control scheme consists of two adaptive fuzzy logic controllers for speed and direct current control, respectively. On the other hand, an Artificial Neural Network (ANN) based observer is used to estimate rotor speed and the rotor position is obtained by using integration to reduce...
This paper introduces a simple adaptive fuzzy controller structure for permanent magnet synchronous machines (PMSMs). Unlike many PMSM-based control techniques, the proposed strategy achieves tracking with no current loop regulation which yields reduced complexity. A simple and effective method is used to set d-axis voltage of the machine to achieve good machine's efficiency. The control scheme and...
In this work, a fuzzy logic control system is proposed for PMSMs without knowledge of the machine's parameters. The scheme consists of two adaptive fuzzy controllers, respectively for velocity and direct current control. The control scheme stability is proven by the Lyapunov stability theory and its performance is validated through a set of simulations on an experimentally validated PMSM model. The...
A hybrid control system for PMSM that requires rough knowledge of the machine's quadrature inductance only is proposed. The scheme consists of an adaptive fuzzy speed controller and a sliding mode current controller. Lyapunov stability conditions are used to design the controllers that result into low sensitivity to torque disturbances and parameter variations.
In this paper, an adaptive fuzzy control scheme is introduced for permanent magnet synchronous machines (PMSMs). The adaptive control strategy consists of a Lyapunov stability-based fuzzy speed controller that capitalizes on the machine's inverse model to achieve accurate tracking with unknown nonlinear system dynamics. As such, robustness to modeling and parametric uncertainties is achieved. Moreover,...
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