A Nonlinear Least-Squares Approach for Identi cation of the Induction Motor Parameters

—A nonlinear least-squares method is presented for the identi cation of the induction motor parameters. A major dif culty with the induction motor is that the rotor state variables are not available measurements so that the system identi cation model cannot be made linear in the parameters without overparametrizing the model. Previous work in the literature has avoided this issue by making simplifying assumptions such as a “slowly varying speed”. Here, no such simplifying assumptions are made. The problem is formulated as a nonlinear leastsquares identi cation problem and uses elimination theory (resultants) to compute the parameter vector that minimizes the residual error. The only requirement is that the system must be suf ciently excited. The method is suitable for online operation to continuously update the parameter values. Experimental results are presented. Index Terms—Least-Squares Identi cation, Induction Motor, Parameter Identi cation, Resultants