High-performance induction motor drive based on adaptive super-twisting sliding mode control approach

This paper proposes two high-order sliding mode algorithms to achieve highperformance control of induction motor drive. In the first approach, the super-twisting algorithm (STA) is used to reduce the chattering effect and to improve control accuracy. The second approach combines the super-twisting algorithm with a quasi-barrier function technique. While the super-twisting algorithm (STA) aims at the chattering reduction, the Barrier super-twisting algorithm (BSTA) aims to eliminate this phenomenon by providing continuous output control signals. The BSTA is designed to prevent the STA gain from being over-estimated by making these gains to decrease and increase according to system's uncertainties. Stability and finite-time convergence are guaranteed using Lyapunov's theory. In addition, the two controlled variables, rotor speed, and rotor flux modulus are estimated based on the second-order sliding mode (SOSM) observer. Finally, simulations are carried out to compare the performance and robustness of two control algorithms without adding the equivalent control. Tests are achieved under external load torque, varying reference speed, and parameter variations.