Abstract
This paper aims at systematically addressing the two fundamental side effects induced inevitably by low-pass filtering: the phase lag and the low-frequency residual measurement errors. A novel two-module-structured robust feedback control framework is proposed, where a phase lag compensator and a measurement error estimator are incorporated. Both modules are designed based on the closed-loop system model in the frequency domain to generate the estimation signals for the phase lag and low-frequency residual errors, respectively. Then, two compensation signals (corresponding to the two estimation signals) are introduced in the controller to cancel out the phase lag and residual errors. Stability and performance analysis is provided based on a servomotor positioning system design example. Comparative simulation results are provided to show the advantages of the proposed approach over other classic approaches.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Bose, B.K., Patel, N.R.: A programmable cascaded low-pass filter-based flux synthesis for a stator flux-oriented vector-controlled induction motor drive. IEEE Trans. Industr. Electron. 44(1), 140–143 (1997)
Shin, M.H., Hyun, D.S., Cho, S.B., Choe, S.Y.: An improved stator flux estimation for speed sensorless stator flux orientation control of induction motors. IEEE Trans. Power Electron. 15(2), 312–318 (2000)
Chun, T.W., Tran, Q.V., Lee, H.H., Kim, H.G.: Sensorless control of BLDC motor drive for an automotive fuel pump using a hysteresis comparator. IEEE Trans. Power Electron. 29(3), 1382–1391 (2013)
Aggarwal, P., Syed, Z., Niu, X., El-Sheimy, N.: A standard testing and calibration procedure for low cost MEMS inertial sensors and units. J. Navigation 61(2), 323–336 (2008)
Wang, F.Y.: The exact and unique solution for phase-lead and phase-lag compensation. IEEE Trans. Educ. 46(2), 258–262 (2003)
Li, L., Jia, X., Chi, X., Yan, W.: An improved tracking differentiator capable of compensating phase lag. In: International Conference on Automatic Control and Artificial Intelligence (ACAI 2012), pp. 457–460. IET (2012)
Zhu, Y., Zhu, B., Liu, H.H.T., Qin, K.Y.: A model-based approach for measurement noise estimation and compensation in feedback control systems. IEEE Trans. Instrum. Meas. 69(10), 8112–8127 (2020)
Gui, P., Tang, L., Mukhopadhyay, S.: MEMS based IMU for tilting measurement: Comparison of complementary and Kalman filter based data fusion. In: 2015 IEEE 10th Conference on Industrial Electronics and Applications (ICIEA), pp. 2004–2009. IEEE (2015)
Khalil, H.K.: Nonlinear Systems, 3rd edn. Prentice-Hall, New Jersey (1996)
Zhong, Q.C., Rees, D.: Control of uncertain LTI systems based on an uncertainty and disturbance estimator. J. Dyn. Syst. Meas. Contr. 126(4), 905–910 (2004)
Acknowledgment
This work was supported by the National Natural Science Foundation of China under Grant 61873215.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Zhu, Y., Xu, L., Zhang, X., Yan, F. (2023). Model-Based Compensation for Phase Lag and Residual Measurement Error Induced by Low-Pass Filtering in Feedback Control Systems. In: Yan, L., Duan, H., Deng, Y. (eds) Advances in Guidance, Navigation and Control. ICGNC 2022. Lecture Notes in Electrical Engineering, vol 845. Springer, Singapore. https://doi.org/10.1007/978-981-19-6613-2_650
Download citation
DOI: https://doi.org/10.1007/978-981-19-6613-2_650
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-19-6612-5
Online ISBN: 978-981-19-6613-2
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)