(untitled) (REVUE ROUMAINE DES SCIENCES TECHNIQUES — SÉRIE ÉLECTROTECHNIQUE ET ÉNERGÉTIQUE, 2024)
This paper focuses on developing two innovative induction motor (IM) control techniques. These techniques are based on the hybridization of Lyapunov theory (sliding mode) and artificial intelligence (type 1 and type 2 fuzzy logic). We will then compare these two control techniques to determine which is more robust. This comparative analysis will be based on a series of tests that we have carried out, covering the system’s transient and steady-state operations under identical conditions. The first test involves observing the simulation results obtained by applying these control techniques to the motor to control the generated mechanical power. This qualitative comparison enables these controls to be evaluated for and without the application of external variations. The second test quantifies the different control laws based on quantified measurements, highlighting the performance of each technique in terms of error and time. This test is called a quantitative comparison. Finally, the last examination involves altering the machine parameters, as these values naturally experience fluctuations caused by diverse physical phenomena like inductance saturation and heating of the resistors. This comparison enables the robustness of the control techniques to be assessed.