2 research outputs found
Real time implementation of a super twisting control of a BLDC motor
This paper presents and implements a Super-Twisting high order sliding mode control for a BLDC motor. Conventional sliding mode controller has a very fast response, it allows the convergence in finite time and characterized by its robustness against disturbances and uncertainties; However, the chattering phenomenon due to the discontinuous nature of its control organ degrades its performance, especially in case of mechanical membranes control. To overcome this disadvantage, the most commun solutions are based on the adaptation of its discontinuous nature at static regime, it reduces effectively the chattering phenomenon, but on the other hand impacts performance in terms of robustness. The Super-Twisting is an algorithm of high order sliding mode applicable on systems with relative degree 1, it produces a continuous control which cancels the chattering phenomenon and preserve all traditional sliding mode command performances. To validate the effectiveness and the robustness of the Super-Twisting controller for controlling brushless motors, experimental results using a 3KW BLDC motor are provided and compared with those of a conventional sliding mode controller
A Robust Interval Type-2 Fuzzy Logic Controller for Variable Speed Wind Turbines Based on a Doubly Fed Induction Generator
This paper presents an implementation of a new robust control strategy based on an interval type-2 fuzzy logic controller (IT2-FLC) applied to the wind energy conversion system (WECS). The wind generator used was a variable speed wind turbine based on a doubly fed induction generator (DFIG). Fuzzy logic concepts have been applied with great success in many applications worldwide. So far, the vast majority of systems have used type-1 fuzzy logic controllers. However, T1-FLC cannot handle the high level of uncertainty in systems (complex and non-linear systems). The amount of uncertainty in a system could be reduced by using type-2 fuzzy logic since it offers better capabilities to handle linguistic uncertainties by modeling vagueness and unreliability of information. A new concept based on an interval type-2 fuzzy logic controller (IT-2 FLC) was developed because of its uncertainty management capabilities. Both these control strategies were designed and their performances compared for the purpose of showing the control most efficient in terms of reference tracking and robustness. We made a comparison between the performance of the type-1 fuzzy logic controller (T1-FLC) and interval type-2 fuzzy logic controller (IT2-FLC). The simulation results clearly manifest the height robustness of the interval type-2 fuzzy logic controller in comparison to the T1-FLC in terms of rise time, settling time, and overshoot value. The simulations were realized by MATLAB/Simulink software