The research presented in this thesis involves different aspects related to advanced control methodologies and self-commissioning identification algorithms in modern electrical drives. The theoretical study and the validation of the results obtained were performed in the three years of Ph.D. at the Electric Drives Laboratory in the Department of Management and Engineering of the University of Padova, (VI) Italy. The research topics were mainly three, all related to the implementation and development of advanced controls for electric drives, aimed at a more efficient use of the electric machines in the modern mechatronic applications. The demand of electric drives capable of guarantee high-performance and flexible enough to update in real time the parameters involved in the control algorithm are the motivation of the present research, as well as the meshing or replacement of standard or obsolete control techniques with modern ones, able to fully exploit the new hardware resources. In order to contextualizes and motivate the choice of the present research in the world scenario, a comprehensive bibliographic framework can be found in the introduction of each chapter of the thesis. The part one of the thesis presents two new control architectures for Permanent Magnet Synchronous Motors, that is a type of electric machine notoriously appreciated by both academia and industry for its flexibility of use and controllability. To this aim, in Chap.2 is proposed a non-linear control algorithm for the automatic search of the Maximum Torque Per Ampere (MTPA) operating condition for Permanent Magnet Synchronous Motors with anisotropic structure, to be integrated in a conventional Field Oriented Control scheme. The exhaustive convergence and stability analysis performed in order to derive a new and original tuning method of the controller (proven by numerous experimental evidences) is definitely one of the distinguishing features in this research topic. In parallel to the first topic, for the same type of motor has been investigated and developed (first analytically and then by simulation) a speed and current Direct Predictive Control with Hierarchical decisional structure. Unlike the traditional control techniques, the proposed Direct Predictive Control with modified hierarchical control structure has a faster dynamic and the capability to impose different operating conditions aimed at the energy efficiency optimisation. The on-line execution of the algorithm required for the experimental validation, has become possible thanks to the adoption of a control platform based on FPGA logic (Chap.3). In fact, the processing speed provided by these devices, released from the execution of sequential instructions (typical of the architecture of the microprocessors), ensures an execution time of the algorithm contained in a few us. The part two of the thesis (i. e. Chap.5) presents an innovative technique of parameter identification for induction motors, capable of estimating the parameters of the equivalent inverse-Gamma electric circuit completely at standstill. As known, the saturations in the parameters of the magnetic circuit of the induction motor and the relative nonlinearities, deteriorate the performance of the standard sensored or sensorless vectorial controls. The studied self-commissioning procedure addresses and solves many problems related to the estimate of the non-linearity of the parameters, and then it can be considered as an evolution of the classical identification techniques in the literature. The practical feasibility, doubly validated by numerous experimental tests and by many finite element simulations on three different induction motors, concludes the chapter and proves definitely the method.