Abstract
A comparative study of the conventional fixed gain PI and Fuzzy Logic based adaptation mechanisms for estimating the stator resistance in a Model Reference Adaptive System (MRAS) based sensorless induction motor drive is investigated here. The rotor speed is estimated parallely by means of a PI control based adaptive mechanism and the electromagnetic torque is also estimated to add more resilience. By considering the external Load torque perturbation as a model perturbation on the estimated stator resistance, the effects of the same on the estimated parameters are observed. The superiority of the Fuzzy based stator resistance adaptation mechanism is observed through detailed simulation performed offline using Matlab/Simulink blocksets. Furthermore, a sensitivity analysis of the stator resistance estimate with respect to load torque is also done to verify the effectiveness of the above concept.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsAbbreviations
- \({\text{i}}_{\text{ds}}^{\text{S}} ,\;{\text{i}}_{\text{qs}}^{\text{S}}\) :
-
d and q axis stator currents in stationary reference frame
- \({\hat{\uppsi }}_{\text{qrV}}^{\text{S}} ,\;{\hat{\uppsi }}_{\text{drV}}^{\text{S}}\) :
-
d and q axis Voltage model rotor flux linkages in stationary reference frame
- \({\hat{\uppsi }}_{\text{qrI}}^{\text{S}} ,\;{\hat{\uppsi }}_{\text{drI}}^{\text{S}}\) :
-
d and q axis Current model rotor flux linkages in stationary reference frame
- Lr, Lm, Ls, σ:
-
Rotor Magnetising and Stator inductance, Reactance
- \({\text{R}}_{\text{S}} ,\;{\hat{\text{R}}}_{\text{S}}\) :
-
Actual and Estimated Stator resistances
- \({\upomega}_{\text{r}} ,{\hat{\upomega}}_{\text{r}} ,{\text{T}}_{\text{r}}\) :
-
Actual and Estimated Rotor speeds, Rotor Time constant
- Kp, KI :
-
Proportional and Integral gains
References
Marcetic, D.P., Krcmar, I.R., Gecic, M.A., Matic, P.R.: Discrete Rotor Flux and Speed Estimators for High-Speed Shaft-Sensorless IM Drives. IEEE T Ind Electron, 61, 3099–3108 (2014).
Smith, A.N., Gadoue, S.M., Finch, J.W.: Improved Rotor Flux Estimation at Low Speeds for Torque MRAS-Based Sensorless Induction Motor Drives. IEEE T Energy Conver, PP, 1–13 (2015).
Schauder, C.: Adaptive Speed Identification for Vector Control of Induction Motors without Rotational Transducers. IEEE T Ind App, 28, 1054–1061 (1992).
Zhao, L., Huang, J., Liu, H., Kong, W.: Second-Order Sliding-Mode Observer With Online Parameter Identification for Sensorless Induction Motor Drives. IEEE T Ind Electron, 61, 5280–5289 (2014).
Vasic, V., Vukosavic, S.N., Levi, E.: A Stator Resistance Estimation Scheme for Speed Sensorless Rotor Flux Oriented Induction Motor Drives, IEEE T Energy Conver, 18, 476–483 (2003).
Zaky, M.S.: A Stable Adaptive Flux Observer for a very low Speed-Sensorless Induction Motor Drive Insensitive to Stator Resistance Variations, Ain Shams Engg J, 2, 11–20 (2011).
Orlowska-Kowalska, T., Dybkowski, M.: Stator – Current-Based MRAS Estimator for a Wide Range Speed-Sensorless Induction-Motor Drive. IEEE T Ind Electron, 57(4), 1296–1308 (2010).
Kubota, H., Matsuse, K.: DSP-Based Speed Adaptive Flux Observer of Induction Motor, IEEE T Ind App, 29(2), 344–348 (1993).
Maiti, S., Chakraborty, C., Hori, Y., Minh C. Ta.: Model Reference Adaptive Controller-Based Rotor Resistance and Speed Estimation Techniques for Vector Controlled Induction Motor Drive Utilizing Reactive Power. IEEE T Ind Electron, 55(2), 594–601 (2008).
Umanand, L., Bhat, S.R.: Online Estimation of Stator Resistance of an Induction Motor for Speed Control Applications. In: Proc. Inst. Elect. Eng.-Elect. Power Applications, 142(2), pp. 97–103 (1995).
Tsuji, M., Chen, S., Izumi, K., Yamada, E.: A Sensorless Vector Control System for Induction Motors using Q-axis Flux with Stator Resistance Identification. IEEE T Ind Electron, 48, 185–194 (2001).
Guidi, G., Umida, H.: A Novel Stator Resistance Estimation Method for Speed-Sensorless Induction Motor Drives. IEEE T Ind App, 36, 1619–1627 (2000).
Raison, B., Arza, J., Rostaing, G., Rognon, J.P.: Comparison of Two Extended Observers for the Resistance Estimation of an Induction Machine. In: Proc. IEEE IAS Annual Meeting (2000).
Mir, S., Elbuluk, M.E., Zinger, D.S.: PI and Fuzzy Estimators for Tuning the Stator Resistance in Direct Torque Control of Induction Machines. IEEE T Power Electr, 13, 279–287 (1998).
Zhen, L., Xu, L.: Sensorless Field Orientation Control of Induction Machines based on a Mutual MRAS scheme, IEEE T Ind Electron, 45, 824–831 (1998).
Haron, A.R., Idris, N.R.N.: Simulation of MRAS-based Speed Sensorless Estimation of Induction Motor Drives using MATLAB/SIMULINK. In: Proc. First International Power and Energy Conference, pp. 411–415 (2006).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Appendix
Appendix
The motor model used in the simulation has the following ratings: A 50HP, three-phase, 415 V, 50 Hz, star connected, four-pole induction motor with equivalent parameters: RS = 0.087 Ω, Rr = 0.228 Ω, Lls = Llr = 0.8 mH, Lm = 34.7 mH, Inertia, J = 1.662 kg m2, friction factor = 0.1.
Rights and permissions
Copyright information
© 2017 Springer Science+Business Media Singapore
About this paper
Cite this paper
Mohan Krishna, S., Febin Daya, J.L. (2017). An Improved Stator Resistance Adaptation Mechanism in MRAS Estimator for Sensorless Induction Motor Drives. In: Mandal, J., Satapathy, S., Sanyal, M., Bhateja, V. (eds) Proceedings of the First International Conference on Intelligent Computing and Communication. Advances in Intelligent Systems and Computing, vol 458. Springer, Singapore. https://doi.org/10.1007/978-981-10-2035-3_38
Download citation
DOI: https://doi.org/10.1007/978-981-10-2035-3_38
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-2034-6
Online ISBN: 978-981-10-2035-3
eBook Packages: EngineeringEngineering (R0)