This paper deals with optimal control strategies robustified by a decoupling super-twisting sliding mode control (ST-SMC) for permanent magnet synchronous machines (PMSM). In general, ST-SMC is a robust method for controlling systems and guarantees asymptotic convergence in cases where the upper bound of model uncertainties such as disturbances and parametric uncertainties is not known a priori, if the upper bound of the derivative is known. The proposed optimal control strategy is designed for a constant torque reference whose control is implemented in two control regions: maximum torque per ampere (MTPA) and flux-weakening control. In the proposed analysis, the operating point of the motor can also be in the saturation region, which makes the estimation of Ld and Lq in the proposed optimization procedure of particular interest and also important for the decoupling control implemented with ST-SMC. To compensate for typical parameter variations, adaptive parameter estimation is introduced into the control system using an extended Kalman filter (EKF) in combination with a bivariate polynomial. In order to be able to make an assessment of the control performance of the ST-SMC, a comparison with a conventional PI controller is shown at the end of the paper. Measured results using hardware in the loop (HIL) to validate the results and their detailed discussion and analysis are included.