Robust Maximum Torque per Ampere (MTPA) control of Interior Permanent Magnet Synchronous motor drives using Adaptive Input-Output Feedback Linearization approach

Recently, interior permanent magnet synchronous motor (IPMSM) drives are getting more popular in many applications such as electrical vehicles. In order to achieve maximum torque per ampere (MTPA), knowledge of the motor parameters is necessary. Due to the saturation effect, variation of the motor parameters such as inductances is not avoidable. The main contribution of this paper is to use the well known adaptive input-output feedback linearization (AIOFL) technique for robust MTPA control of IPMSM with online simultaneous estimation of direct and quadrature axis inductances (Ld, Lq). The overall stability of this controller is analytically proved based on Lyapunov theory. It is found that under persistency of excitation (PE) condition, the errors of two-axis fluxes and as well as the estimation errors in parameters Ld and Lq asymptotically converge to zero. In addition, the variation of stator resistance due to changes in temperature or frequency degrades the performance of stator linkage flux estimator and controller. Online estimation of the stator resistance using a PI estimator is also employed in this paper. The simulation results obtained confirm that the proposed method is capable of maintaining the MTPA condition and stays robust against the motor parameters variations. give you basic guidelines for preparing papers for conference proceedings.