This paper presents a novel approach for estimation of mechanical parameters, inertia and friction coefficient of an Induction Machine (IM) using speed loop characteristics and Recursive Least Square (RLS) estimator. Using the 5th order dynamic equation for Induction Machine and the forgetting factor based RLS algorithm the technique herein proposed employs the speed of the machine and the torque as the inputs for the estimator. Results obtained compares the estimated parameters with the actual parameters under multiple step varying and exponentially varying scenarios. Upon analyzing the results, the validity and the effectiveness of the proposed identification technique is confirmed
Prasad, R., Chand, S., Mudaliar, H., Kumar, D., Fagiolini, A., Di Benedetto, M., et al. (2022). Online Estimation of the Mechanical Parameters of an Induction Machine Using Speed Loop characteristics and Recursive Least Square Technique. In Proceedings of the 2022 25th International Conference on Electrical Machines and Systems (ICEMS) (pp. 1-5). Institute of Electrical and Electronics Engineers Inc. [10.1109/ICEMS56177.2022.9983277].
Online Estimation of the Mechanical Parameters of an Induction Machine Using Speed Loop characteristics and Recursive Least Square Technique
Mudaliar, Hiye;Kumar, Dhirendran;Fagiolini, Adriano;
2022-11-29
Abstract
This paper presents a novel approach for estimation of mechanical parameters, inertia and friction coefficient of an Induction Machine (IM) using speed loop characteristics and Recursive Least Square (RLS) estimator. Using the 5th order dynamic equation for Induction Machine and the forgetting factor based RLS algorithm the technique herein proposed employs the speed of the machine and the torque as the inputs for the estimator. Results obtained compares the estimated parameters with the actual parameters under multiple step varying and exponentially varying scenarios. Upon analyzing the results, the validity and the effectiveness of the proposed identification technique is confirmed
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