A comparative study of DC servo motor parameter estimation using various techniques

References

• Usman HM, Mukhopadhyay S, Rehman H. Permanent magnet DC motor parameters estimation via universal adaptive stabilization. Control Eng Pract. Sep. 2019;90:50–62. doi:https://doi.org/10.1016/j.conengprac.2019.06.006.
   Web of Science ®Google Scholar
• Kommuri SK, Defoort M, Karimi HR, et al. A robust observer-based sensor fault-tolerant control for PMSM in electric vehicles. IEEE Trans Ind Electron. Dec. 2016;63(12):7671–7681. doi:https://doi.org/10.1109/TIE.2016.2590993.
   Web of Science ®Google Scholar
• Das D, Kumaresan N, Nayanar V, et al. Development of BLDC motor-based elevator system suitable for DC microgrid. IEEE/ASME Trans Mechatron. Jun. 2016;21(3):1552–1560. doi:https://doi.org/10.1109/TMECH.2015.2506818.
   Web of Science ®Google Scholar
• Chaoui H, Khayamy M, Aljarboua AA. Adaptive interval type-2 fuzzy logic control for PMSM drives with a modified reference frame. IEEE Trans Ind Electron. May 2017;64(5):3786–3797. doi:https://doi.org/10.1109/TIE.2017.2650858.
   Web of Science ®Google Scholar
• Li P, Zhu G. Robust internal model control of servo motor based on sliding mode control approach. ISA Trans. Oct. 2019;93:199–208. doi:https://doi.org/10.1016/j.isatra.2019.03.021.
   PubMed Web of Science ®Google Scholar
• Xie Y, Tang X, Song B, et al. Data-driven adaptive fractional order PI control for PMSM servo system with measurement noise and data dropouts. ISA Trans. Apr. 2018;75:172–188. doi:https://doi.org/10.1016/j.isatra.2018.02.018.
   PubMed Web of Science ®Google Scholar
• Shi D, Xue J, Zhao L, et al. Event-triggered active disturbance rejection control of DC torque motors. IEEE/ASME Trans Mechatron. Oct. 2017;22(5):2277–2287. doi:https://doi.org/10.1109/TMECH.2017.2748887.
   Web of Science ®Google Scholar
• Mwasilu F, Nguyen HT, Choi HH, et al. Finite set model predictive control of interior PM synchronous motor drives with an external disturbance rejection technique. IEEE/ASME Trans Mechatron. Apr. 2017;22(2):762–773. doi:https://doi.org/10.1109/TMECH.2016.2632859.
   Web of Science ®Google Scholar
• Ghosh M, Panda GK, Saha PK. Analysis of chaos and bifurcation due to slotting effect and commutation in a current discontinuous permanent magnet brushed DC motor drive. IEEE Trans Ind Electron. Mar. 2018;65(3):2001–2008. doi:https://doi.org/10.1109/TIE.2017.2745446.
   Web of Science ®Google Scholar
• Meng F, Chen H, Zhang T, et al. Clutch fill control of an automatic transmission for heavy-duty vehicle applications. Mech Syst Signal Process. Dec. 2015;64–65:16–28. doi:https://doi.org/10.1016/j.ymssp.2015.02.026.
   Web of Science ®Google Scholar
• Song X, Sun Z. Pressure-based clutch control for automotive transmissions using a sliding-mode controller. IEEE/ASME Trans Mechatron. Jun. 2012;17(3):534–546. doi:https://doi.org/10.1109/TMECH.2011.2106507.
   Web of Science ®Google Scholar
• Gao B, Chen H, Liu Q, et al. Position control of electric clutch actuator using a triple-step nonlinear method. IEEE Trans Ind Electron. Dec. 2014;61(12):6995–7003. doi:https://doi.org/10.1109/TIE.2014.2317131.
   Web of Science ®Google Scholar
• Li G, Tsang KM. Concurrent relay-PID control for motor position servo systems. 2007.
   Google Scholar
• Bindu R, Namboothiripad MK. Tuning of PID controller for DC servo motor using genetic algorithm. 2012.
   Google Scholar
• Wang X, Wang W, Li L, et al. Adaptive control of DC motor servo system with application to vehicle active steering. IEEE/ASME Trans Mechatron. Jun. 2019;24(3):1054–1063. doi:https://doi.org/10.1109/TMECH.2019.2906250.
   Web of Science ®Google Scholar
• Ohnishi K, Katsura S, Shimono T. Motion control for real-world haptics. IEEE Ind Electron Mag. Jun. 2010;4(2):16–19. doi:https://doi.org/10.1109/MIE.2010.936761.
   Web of Science ®Google Scholar
• Ma H, Zhou Q, Bai L, et al. Observer-based adaptive fuzzy fault-tolerant control for stochastic nonstrict-feedback nonlinear systems with input quantization. IEEE Trans Syst Man Cybern Syst. Feb. 2019;49(2):287–298. doi:https://doi.org/10.1109/TSMC.2018.2833872.
   Web of Science ®Google Scholar
• Liu Z, Chen C, Zhang Y. Decentralized robust fuzzy adaptive control of humanoid robot manipulation with unknown actuator backlash. IEEE Trans Fuzzy Syst. Jun. 2015;23(3):605–616. doi:https://doi.org/10.1109/TFUZZ.2014.2321591.
   Web of Science ®Google Scholar
• Fesharaki SJ, Kamali M, Sheikholeslam F. Adaptive tube-based model predictive control for linear systems with parametric uncertainty. IET Control Theory Appl. Aug. 2017;11(17):2947–2953. doi:https://doi.org/10.1049/iet-cta.2017.0228.
   Web of Science ®Google Scholar
• Long J, Wang W, Huang J, et al. Distributed adaptive control for asymptotically consensus tracking of uncertain nonlinear systems with intermittent actuator faults and directed communication topology. IEEE Trans Cybern. 2019: 1–12. doi:https://doi.org/10.1109/TCYB.2019.2940284.
   Web of Science ®Google Scholar
• Guo Q, Yin J, Yu T, et al. Saturated adaptive control of an electrohydraulic actuator with parametric uncertainty and load disturbance. IEEE Trans Ind Electron. Oct. 2017;64(10):7930–7941. doi:https://doi.org/10.1109/TIE.2017.2694352.
   Web of Science ®Google Scholar
• Lai G, Liu Z, Zhang Y, et al. Asymmetric actuator backlash compensation in quantized adaptive control of uncertain networked nonlinear systems. IEEE Trans Neural Netw Learn Syst. Feb. 2017;28(2):294–307. doi:https://doi.org/10.1109/TNNLS.2015.2506267.
   PubMed Web of Science ®Google Scholar
• Zhu Y, Su H, Krstic M. Adaptive backstepping control of uncertain linear systems under unknown actuator delay. Automatica. Apr. 2015;54:256–265. doi:https://doi.org/10.1016/j.automatica.2015.02.013.
   Web of Science ®Google Scholar
• Arefi MM, Zarei J, Karimi HR. Adaptive output feedback neural network control of uncertain non-affine systems with unknown control direction. J Franklin Inst. Aug. 2014;351(8):4302–4316. doi:https://doi.org/10.1016/j.jfranklin.2014.05.006.
   Web of Science ®Google Scholar
• Zhou J, Wen C, Zhang Y. Adaptive backstepping control of a class of uncertain nonlinear systems with unknown backlash-like hysteresis. IEEE Trans Autom Control. Oct. 2004;49(10):1751–1759. doi:https://doi.org/10.1109/TAC.2004.835398.
   Web of Science ®Google Scholar
• Lu Z, Huang P, Liu Z. Predictive approach for sensorless bimanual teleoperation under random time delays with adaptive fuzzy control. IEEE Trans Ind Electron. Mar. 2018;65(3):2439–2448. doi:https://doi.org/10.1109/TIE.2017.2745445.
   Web of Science ®Google Scholar
• Zhao X, Yang H, Karimi HR, et al. Adaptive neural control of MIMO nonstrict-feedback nonlinear systems with time delay. IEEE Trans Cybern. Jun. 2016;46(6):1337–1349. doi:https://doi.org/10.1109/TCYB.2015.2441292.
   PubMed Web of Science ®Google Scholar
• Zhou J, Wang W. Adaptive control of quantized uncertain nonlinear systems. IFAC-PapersOnLine. Jul. 2017;50(1):10425–10430. doi:https://doi.org/10.1016/j.ifacol.2017.08.1970.
   Google Scholar
• Manikandan S, Kokil P. Stability analysis of network-controlled DC position servo system with time-delay. Automatika. Apr. 2021;62(2):163–171. doi:https://doi.org/10.1080/00051144.2020.1800265.
   Web of Science ®Google Scholar
• Salas-Peña O, Castañeda H, de León-Morales J. Robust adaptive control for a DC servomotor with wide backlash nonlinearity. Automatika. Jan. 2015;56(4):436–442. doi:https://doi.org/10.1080/00051144.2015.11828657.
   Web of Science ®Google Scholar
• Xudong Y. Nonlinear adaptive learning control with disturbance of unknown periods. IEEE Trans Autom Control. May 2012;57(5):1269–1273. doi:https://doi.org/10.1109/TAC.2011.2173414.
   Web of Science ®Google Scholar
• Ortega R, Praly L, Aranovskiy S, et al. On dynamic regressor extension and mixing parameter estimators: two Luenberger observers interpretations. Automatica. Sep. 2018;95:548–551. doi:https://doi.org/10.1016/j.automatica.2018.06.011.
   Web of Science ®Google Scholar
• Aranovskiy S, Bobtsov A, Ortega R, et al. Performance enhancement of parameter estimators via dynamic regressor extension and mixing*. IEEE Trans Autom Control. Jul. 2017;62(7):3546–3550. doi:https://doi.org/10.1109/TAC.2016.2614889.
   Web of Science ®Google Scholar
• Belov A, Aranovskiy S, Ortega R, et al. Enhanced parameter convergence for linear systems identification: The DREM approach*. 2018 European Control Conference (ECC); 2018 Jun. p. 2794–2799. doi:https://doi.org/10.23919/ECC.2018.8550338.
   Google Scholar
• Yi B, Ortega R, Zhang W. Relaxing the conditions for parameter estimation-based observers of nonlinear systems via signal injection. Syst Control Lett. Jan. 2018;111:18–26. doi:https://doi.org/10.1016/j.sysconle.2017.10.011.
   Web of Science ®Google Scholar
• Ortega R, Bobtsov A, Pyrkin A, et al. A parameter estimation approach to state observation of nonlinear systems. Syst Control Lett. Nov. 2015;85:84–94. doi:https://doi.org/10.1016/j.sysconle.2015.09.008.
   Web of Science ®Google Scholar
• Na J, Xing Y, Costa-Castelló R. Adaptive estimation of time-varying parameters with application to roto-magnet plant. IEEE Trans Syst Man Cybern Syst. Feb. 2021;51(2):731–741. doi:https://doi.org/10.1109/TSMC.2018.2882844.
   Web of Science ®Google Scholar
• DC Servo Motor Parameter Estimation – MATLAB & Simulink – MathWorks India. [cited 2020 Jan 16]. https://in.mathworks.com/help/sldo/examples/dc-servo-motor-parameter-estimation.html?s_tid=mwa_osa_a.
   Google Scholar