Identification of self-tuning induction motor drive system based on improved least-square algorithm

The variation of the load inertia influences the dynamic performance of an AC servo system significantly. In this paper, an improved recursive least-squares (RLS) method with a particular detection unit is presented for the identification. Once a variation of the inertia is detected, the unit re-initialize the algorithm to ensure the fast response. Furthermore, if proper simplifications and assumptions are accepted, the speed loop of the servo system can be regarded as a typical type-II system, which makes it possible to link the current loop factors with the inertia. Thus, the self-tuning control of the system is improved. Simulation results demonstrate the proposed scheme is effective.