Adviser: Ming-Shyan Wang Student: Feng-Chi Lin

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Adviser: Ming-Shyan Wang Student: Feng-Chi Lin Design of Iterative Sliding Mode Observer for Sensorless PMSM Control Hyun Lee and Jangmyung Lee IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, VOL. 21, NO. 4, JULY 2013 1394-1399 Adviser: Ming-Shyan Wang Student: Feng-Chi Lin 2018/6/15

Robot and Servo Drive Lab. OUTLINE Abstract Modeling of PMSM Proposed ISMO System Configuration Experimental Results Conclusion References 2018/6/15 Robot and Servo Drive Lab.

Robot and Servo Drive Lab. Abstract This brief proposes an iterative sliding mode observer (ISMO) for the robust sensorless control of a permanent magnet synchronous motor with variable Parameters。 In the conventional SMO, a low-pass filter and an additional position compensator for the rotor are used to reduce the chattering coming from the switching by means of a signum function。 It is shown that the chattering can be further reduced by using a sigmoid function as the switching function in the observer。 The proposed ISMO also improves the performance in estimating the motor speed and angle by reducing the estimation error in the back electromotive force by iteratively applying the observer in the sensorless operation。 2018/6/15 Robot and Servo Drive Lab.

Robot and Servo Drive Lab. Modeling of PMSM (1) (2) 2018/6/15 Robot and Servo Drive Lab.

Robot and Servo Drive Lab. Proposed ISMO A. Conventional SMO Fig. 1. PMSM sensorless control system with conventional SMO (3) , is the reference speed of the rotor, f is the cutoff frequency for the filter, and are the angular frequencies at rotor speeds of and , respectively 2018/6/15 Robot and Servo Drive Lab.

Robot and Servo Drive Lab. Proposed ISMO B. Sigmoid Function (4) Fig. 2. Improved SMO with sigmoid function (5) 2018/6/15 Robot and Servo Drive Lab.

Robot and Servo Drive Lab. Proposed ISMO The sliding surface is defined as (6) The Lyapunov function candidate is defined as (7) From (2) and (4), the error equations are derived as (8) 2018/6/15 Robot and Servo Drive Lab.

Robot and Servo Drive Lab. Proposed ISMO To satisfy the existence condition of the sliding mode , (9) (10) This sigmoid function requires an observer gain k, which is a constant value between −kmax and kmax, to satisfy the Lyapunov stability condition (9) 2018/6/15 Robot and Servo Drive Lab.

Robot and Servo Drive Lab. Proposed ISMO With the predetermined observer gain k, the sliding mode may exist on the sliding surface as follows: (11) (12) Using the sigmoid function, the sliding mode control becomes continuous, which reduces the chattering. The estimation of the back EMF in (12) can be used to estimate the position and velocity of the rotor as follows: (13) 2018/6/15 Robot and Servo Drive Lab.

Robot and Servo Drive Lab. Proposed ISMO Fig. 3. Concept of ISMO Fig. 4. Structure of proposed ISMO. 2018/6/15 Robot and Servo Drive Lab.

Robot and Servo Drive Lab. System Configuration Fig. 5. Block diagram of proposed sensorless speed control system 2018/6/15 Robot and Servo Drive Lab.

Robot and Servo Drive Lab. Experimental Results Fig. 6 2018/6/15 Robot and Servo Drive Lab.

Robot and Servo Drive Lab. Experimental Results Fig. 7. Response times of conventional SMO and ISMO. 2018/6/15 Fig. 8. Comparison of responses against disturbances Robot and Servo Drive Lab.

Robot and Servo Drive Lab. Experimental Results Performance comparison of conventional SMO and ISMO for 2000-rpm motor control. (a) and of SMO with signum function. (b) and of SMO with sigmoid function. (c) and of ISMO (a) 2018/6/15 (b) (c) Robot and Servo Drive Lab.

Robot and Servo Drive Lab. Experimental Results 2018/6/15 Fig. 9. Estimation performance of stator resistance variations Robot and Servo Drive Lab.

Robot and Servo Drive Lab. Conclusion In this brief, a sensorless control system for a PMSM was implemented by applying an ISMO. To make it robust against disturbances and parameter variations, the signum function used as a switching function in the conventional SMO was replaced by a sigmoid function. The proposed ISMO was robust and fast, so that the sensorless control system using this ISMO had a fast response and was robust against disturbances. In future works, the observer gains need to be adjusted automatically using intelligent algorithms such as fuzzy interferences 2018/6/15 Robot and Servo Drive Lab.

Robot and Servo Drive Lab. References [1] Z. Yang, S. Hara, S. Kanae, K. Wada, and C. Su, “An adaptive robust nonlinear motion controller combined with disturbance observer,”IEEE Trans. Control Syst. Technol., vol. 18, no. 2, pp. 454–462, Mar.2010. [2] F. Parasiliti, R. Petrella, and M. Tursini, “Sensorless speed control of a PM synchronous motor by sliding mode observer,” in Proc. IEEE Int.Symp. Ind. Electron., vol. 3. Jul. 1997, pp. 1106–1111. [3] S. Chi, Z. Zhang, and L. Xu, “Sliding-mode sensorless control of directdrive PM synchronous motors for washing machine applications,” IEEE Trans. Ind. Appl., vol. 45, no. 2, pp. 582–590, Mar.–Apr. 2009. [4] L. Chang sheng and M. Elbuluk, “A sliding mode observer for sensorless control of permanent magnet synchronous motors,” in Proc. IEEE IAS Annu. Meeting, vol. 2. Sep. 2001, pp. 1273–1278. [5] J. Hu, D. Zhu, Y. Li, and J. Gao, “Application of sliding observer to 2018/6/15 Robot and Servo Drive Lab.

Robot and Servo Drive Lab. References sensorless permanent magnet synchronous motor drive system,” in Proc. IEEE Power Electron. Special. Conf., vol. 1. Jun. 1994, pp. 532–536. [6] P. Vaclavek and P. Blaha, “Lyapunov function-based flux and speed observer for AC induction motor sensorless control and parameters estimation,” IEEE Trans. Ind. Electron., vol. 53, no. 1, pp. 138–145,Feb. 2006. [7] S. Ichikawa, M. Tomita, S. Doki, and S. Okuma, “Sensorless control of permanent-magnet synchronous motors using online parameter identification based on system identification theory,” IEEE Trans. Ind. Electron., vol. 53, no. 2, pp. 363–372, Apr. 2006. [8] X. Yu and O. Kaynak, “Sliding-mode control with soft computing: A survey,” IEEE Trans. Ind. Electron., vol. 56, no. 9, pp. 3275–3283, Sep. 2009. [9] V. D. Colli, R. D. Stefano, and M. Scarano, “Gate-level simulation of a 2018/6/15 Robot and Servo Drive Lab.

Robot and Servo Drive Lab. References FPGA-based PMSM drive sensorless control,” in Proc. IEEE Ind. Appl. Conf., Sep. 2007, pp. 1288–1292. [10] F. Genduso, R. Miceli, C. Rando, and G. R. Galluzzo, “Back EMF sensorless-control algorithm for high-dynamic performance PMSM,” IEEE Trans. Ind. Electron., vol. 57, no. 6, pp. 2092–2100, Jun. 2010. [11] H. R. Kim, J. B. Son, and J. M. Lee, “A high-speed sliding-mode observer for the sensorless speed control of a PMSM,” IEEE Trans. Ind. Electron., vol. 58, no. 9, pp. 4069–4077, Sep. 2011. [12] K.-L. Kang, J.-M. Kim, K.-B. Hwang, and K.-H. Kim, “Sensorless control of PMSM in high speed range with iterative sliding mode observer,” in Proc. 19th Annu. Appl. Power Electron. Conf., vol. 2. 2004, pp. 1111–1116. [13] Y. S. Han, J. S. Choi, and Y. S. Kim, “Sensorless PMSM drive with a sliding mode control based adaptive speed and stator resistance 2018/6/15 Robot and Servo Drive Lab.

Robot and Servo Drive Lab. References estimator,” IEEE Trans. Magn., vol. 36, no. 5, pp. 3588–3591, Sep. 2000. [14] K. Paponpen and M. Konghirun, “An improved sliding mode observer for speed sensorless vector control drive of PMSM,” in Proc. CES/IEEE 5th Int. Power Electron. Motion Control Conf., vol. 2. Aug. 2006, pp. 1–5. [15] D. Zaltni, M. Ghanes, J. P. Barbot, and M. N. Abdelkrim, “Synchronous motor observability study and an improved zero-speed position estimation design,” in Proc. IEEE Conf. Decision Control, Dec. 2010, pp. 5074–5079. 2018/6/15 Robot and Servo Drive Lab.