<![CDATA[In this study presents a self-tuning type-2 fuzzy logic controller framework, which operates on the principle of continuously adjusting the controller structure by modifying the controller gain (scaling factor) as a function of the error and its rate of change, in order to achieve optimal control performance. The proposed structure is both simple and robust, with real-time gain adaptation facilitated by two type-2 fuzzy systems; the first one containing the rules of control task for speed regulation, and the second one containing the rules for the adaptation of the scaling factor. Both systems have the same inputs error and its variation. This work specifically focuses on tuning the output scaling factor, which is considered equivalent to the controller gain. The effectiveness of the proposed approach is evaluated through its application to the control of an induction machine, a system known for its complexity and strong nonlinearity. Simulation results demonstrate that the fuzzy controller significantly enhances performance, even under challenging operating conditions such as low-speed regimes.]]>
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