Discrete Terminal Super-Twisting Current Control of a Six-Phase Induction Motor

Abstract

In this manuscript, the high-accuracy stator currents tracking issue is considered for a six-phase induction motor subject to external perturbations and uncertainties due to unmeasurable rotor currents and electrical parameter variations. To achieve the control goals, the common two-cascade controllers structure is required for this type of motor. The first controller in the outer loop consists of a proportional integral to regulate the speed. Then, the second is the proposed inner nonlinear stator currents controller based on a robust discrete-time terminal super-twisting algorithm supported by the time-delay estimation method. For the design procedure, the discrete-time stator currents dynamics are derived; for example, the vector of the matched perturbations and unmeasurable rotor currents are specified to simplify the estimation. A detailed stability analysis of the closed-loop error dynamics using Lyapunov theory is given. Finally, a real asymmetrical six-phase induction motor is used to implement in real-time the developed method and to illustrate its effectiveness and robustness. The results obtained reveal a satisfactory stator currents tracking in steady state and transient conditions and under variation in the magnetizing inductance. Moreover, a comparative study with an existing method in steady state for two different rotor speeds is presented to show the superiority of the proposed discrete-time technique.

Recent Advances in Model Predictive and Sliding Mode Current Control Techniques of Multiphase Induction Machines

“…Finally, we exhibit the experimental performance of SMC using the same experimental test-bench as the one obtained used for the results presented in As expected, Figure 14A shows the higher Chattering of classic SMC. We can note that DSMC-ERL (Kali et al, 2019d) shows better performance than the rest in this operating point, while DTSTA (Kali et al, 2021b) has also considerably ripple in some parts. Figure 14E compares DSMC with DSTA using the mean (Kali et al, 2019a), (B) DSMC with Exponential Reaching Law (DSMC-ERL) (Kali et al, 2019d), (C) Discrete-time Super-Twisting Algorithm (DSTA) (Kali et al, 2020a) and (D) Discrete-time Terminal Super-Twisting Algorithm (DTSTA) (Kali et al, 2021b).…”

“…We can note that DSMC-ERL (Kali et al, 2019d) shows better performance than the rest in this operating point, while DTSTA (Kali et al, 2021b) has also considerably ripple in some parts. Figure 14E compares DSMC with DSTA using the mean (Kali et al, 2019a), (B) DSMC with Exponential Reaching Law (DSMC-ERL) (Kali et al, 2019d), (C) Discrete-time Super-Twisting Algorithm (DSTA) (Kali et al, 2020a) and (D) Discrete-time Terminal Super-Twisting Algorithm (DTSTA) (Kali et al, 2021b). (E) Comparative between DSMC and DSTA using Mean Squared Error (MSE) as performance parameter (Kali et al, 2020a).…”

“…This latter allows a finite-time convergence and ameliorates the system's convergence properties during the sliding phase. For this reason, the presented TDE-based DSTA had been enhanced in (Kali et al, 2021b).…”

“…This latter usually occurs in electrical motors because of the heat of the components. The proposed TDEbased Discrete Terminal Super-Twisting Algorithm (DTSTA) (Kali et al, 2021b) has been implemented successfully on a real six-phase IM. The control inputs can be obtained using the algorithms in Eqs 63, 64 for the α − β and the x − y stator currents as follows:…”

“…However, since SMC has its major drawback, the Chattering, many approaches have been studied for other systems and recently implemented for multiphase machines. Some examples include the DSMC with exponential reaching law (Kali et al, 2019d), Discrete-time Super-Twisting Algorithm (DSTA) (Kali et al, 2020a) and Discrete-time Terminal STA (DTSTA) (Kali et al, 2021b). Other more sophisticated nonlinear controllers have also been studied recently.…”