Predefined-Time Super-Twisting Disturbance-Observer-Based Speed Control for PI-Based FOC Induction Motor Drives
DOI:
https://doi.org/10.12928/biste.v8i2.15761Keywords:
Six Phase Induction Motor, Proportional–Integral, Field-Oriented Control, Sliding Mode Control, Super-Twisting AlgorithmAbstract
This paper proposes a predefined-time super-twisting disturbance-observer-based speed control strategy integrated into a conventional proportional–integral (PI)-based Field-Oriented Control (FOC) framework for induction motor drives. Although PI regulators are widely adopted in industrial FOC systems due to their simplicity, low computational burden, and practical reliability, the mechanical speed loop remains vulnerable to load torque variations and parameter uncertainties, resulting in degraded transient performance and limited disturbance rejection capability. To address this issue, a predefined-time super-twisting disturbance observer is incorporated exclusively into the outer speed loop, while standard PI controllers are preserved for current and flux regulation, thereby maintaining structural simplicity and industrial compatibility. Specifically, a nonlinear predefined-time sliding manifold combined with time-varying adaptive gains is constructed to explicitly shape the convergence behavior and guarantee that the speed tracking error converges within a user-defined time independent of initial conditions and without requiring prior knowledge of disturbance bounds. Rigorous Lyapunov analysis establishes predefined-time stability of the disturbance estimation and overall closed-loop system. Simulation results under speed reversals, step load variations, and stochastic disturbances demonstrate that the proposed method achieves faster convergence, reduced overshoot, and enhanced robustness compared with conventional PI-based FOC, while preserving low implementation complexity and practical feasibility for industrial drive applications.
References
M. L. De Klerk and A. K. Saha, "A Comprehensive Review of Advanced Traction Motor Control Techniques Suitable for Electric Vehicle Applications," in IEEE Access, vol. 9, pp. 125080-125108, 2021, https://doi.org/10.1109/ACCESS.2021.3110736.
H. J. Abu-Rub, A. Iqbal, and J. Guzinski. High Performance Control of AC Drives with Matlab/Simulink. Hoboken, NJ, USA: John Wiley & Sons. 2021, https://doi.org/10.1002/9781119591313.
A. El-Shahat. Induction Motors: Recent Advances, New Perspectives and Applications. 2023, https://doi.org/10.5772/intechopen.104031.
M. A. Azab, "A Review of Recent Trends in High-Efficiency Induction Motor Drives," in Vehicles, vol. 7, no. 1, p. 15, 2025, https://doi.org/10.3390/vehicles7010015.
E. B. Agamloh and A. Cavagnino, "High efficiency design of induction machines for industrial applications," in Proc. IEEE Workshop Electr. Mach. Design, Control Diagnosis (WEMDCD), pp. 33-46, 2013, https://doi.org/10.1109/WEMDCD.2013.6525163.
P. C. Krause, O. Wasynczuk, S. D. Sudhoff, and S. Pekarek, Analysis of Electric Machinery and Drive Systems, 3rd ed. Hoboken, NJ, USA: Wiley-IEEE Press, 2013, https://doi.org/10.1002/9781118524336.
R. W. De Doncker, D. W. Pulle, and A. Veltman. Advanced electrical drives: analysis, modeling, control. Springer Nature. 2020. https://doi.org/10.1007/978-3-030-48977-9.
J. K. Jain, S. Ghosh, and S. Maity, "Concurrent PI Controller Design for Indirect Vector Controlled Induction Motor," in Asian Journal of Control, vol. 22, no. 1, pp. 130-142, 2018, https://doi.org/10.1002/asjc.1911.
N. Goel, S. Chacko, and R. Patel, "PI Controller Tuning Based on Stochastic Optimization Technique for Performance Enhancement of DTC Induction Motor Drives," in Journal of the Institution of Engineers (India): Series B, vol. 101, pp. 1-8, 2020, https://doi.org/10.1007/s40031-020-00496-z.
K.-K. Shyu, F.-J. Lin, H.-J. Lin, and B.-S. Juang, "Robust variable structure speed control for induction motor drive," in IEEE Transactions on Aerospace and Electronic Systems, vol. 35, no. 1, pp. 215-224, 1999, https://doi.org/10.1109/7.745693.
J. Wang, F. Wang, Z. Zhang, S. Li, and J. Rodríguez, "Disturbance Compensation-Based Enhanced Robust Finite Control Set Predictive Torque Control for Induction Motor Systems," in IEEE Transactions on Industrial Informatics, vol. 13, no. 5, pp. 2645-2656, 2017, https://doi.org/10.1109/TII.2017.2679283.
S. V. Ustun and M. Demirtas, "Optimal Tuning of PI Coefficients by Using Fuzzy-Genetic Algorithm for V/f Controlled Induction Motor," in Expert Systems with Applications, vol. 34, no. 4, pp. 2714-2720, 2008, https://doi.org/10.1016/j.eswa.2007.05.029.
Q. A. Tarbosh et al., "Review and Investigation of Simplified Rules Fuzzy Logic Speed Controller of High-Performance Induction Motor Drives," in IEEE Access, vol. 8, pp. 49377-49394, 2020, https://doi.org/10.1109/ACCESS.2020.2977115.
W. Shipman and L. Coetzee, "Reinforcement Learning and Deep Neural Networks for PI Controller Tuning," in IFAC-PapersOnLine, vol. 52, no. 29, pp. 111-116, 2019, https://doi.org/10.1016/j.ifacol.2019.09.173.
W. Song, J. Li, C. Ma, Y. Xia, and B. Yu, "A Simple Tuning Method of PI Regulators in FOC for PMSM Drives Based on Deadbeat Predictive Conception," in IEEE Transactions on Transportation Electrification, vol. 10, no. 4, pp. 9852-9863, 2024, https://doi.org/10.1109/TTE.2024.3385114.
R. Marouane and Z. Malika, "Particle Swarm Optimization for Tuning PI Controller in FOC Chain of Induction Motors," in Proc. 4th Int. Conf. Optimization and Applications (ICOA), pp. 1-5, 2018, https://doi.org/10.1109/ICOA.2018.8370512.
R. Arulmozhiyal and K. Baskaran, "Implementation of a Fuzzy PI Controller for Speed Control of Induction Motors Using FPGA," in Journal of Power Electronics, vol. 10, no. 1, pp. 65-71, 2010, https://doi.org/10.6113/JPE.2010.10.1.065.
H. Li, B. Song, T. Chen, Y. Xie, and X. Zhou, "Adaptive fuzzy PI controller for permanent magnet synchronous motor drive based on predictive functional control," in Journal of the Franklin Institute, vol. 358, no. 15, pp. 7333-7364, 2021, https://doi.org/10.1016/j.jfranklin.2021.07.024.
W. Cui, Y. Jiang, B. Zhang, and Y. Shi, "Structured Neural-PI Control with End-to-End Stability and Output Tracking Guarantees," Advances in Neural Information Processing Systems, vol. 36, pp. 68434-68457, 2023, https://doi.org/10.52202/075280-2992.
U. Alejandro-Sanjines, A. Maisincho-Jivaja, V. Asanza, L. Lorente, and D. Peluffo-Ordóñez, "Adaptive PI Controller Based on a Reinforcement Learning Algorithm for Speed Control of a DC Motor," in Biomimetics, vol. 8, no. 5, p. 434, 2023, https://doi.org/10.3390/biomimetics8050434.
I. Djelamda and I. Bouchareb, "Field-oriented control based on adaptive neuro-fuzzy inference system for PMSM dedicated to electric vehicle," in Bulletin of Electrical Engineering and Informatics, vol. 11, no. 4, pp. 1892-1901, 2022, https://doi.org/10.11591/eei.v11i4.3818.
F. Saidi, F. Naceri, L. Youb, M. Cernat, and L. Guasch Pesquer, "Two Types of Fuzzy Logic Controllers for the Speed Control of the Doubly-Fed Induction Machine," in Advances in Electrical and Computer Engineering, vol. 20, no. 3, pp. 65-74, 2020, https://doi.org/10.4316/AECE.2020.03008.
P. Kumar, S. Nema, and P. K. Padhy, "PID controller for nonlinear system using cuckoo optimization," in Proc. Int. Conf. Control, Instrumentation, Communication and Computational Technologies (ICCICCT), pp. 711-716, 2014, https://doi.org/10.1109/ICCICCT.2014.6993052.
H. Goud and P. Swarnkar, “Investigations on Metaheuristic Algorithm for Designing Adaptive PID Controller for Continuous Stirred Tank Reactor: H. Goud, P. Swarnkar,” Mapan, vol. 34, no. 1, pp. 113-119, 2019, https://doi.org/10.1007/s12647-018-00300-w.
Z. Chu, Q. Guo, and C. Wang, "The PID Control Algorithm based on Whale Optimization Algorithm Optimized BP Neural Network," in Proc. IEEE 7th Information Technology and Mechatronics Engineering Conference (ITOEC), pp. 2450-2453, 2023, https://doi.org/10.1109/ITOEC57671.2023.10291531.
I. Kasim and W. Riyadh, "On the Improved Nonlinear Tracking Differentiator based Nonlinear PID Controller Design," in International Journal of Advanced Computer Science and Applications, vol. 7, no. 10, 2016, https://doi.org/10.14569/IJACSA.2016.071032.
S. Nadweh, O. Khaddam, G. Hayek, B. Atieh, and H. H. Alhelou, "Optimization of P & PI controller parameters for variable speed drive systems using a flower pollination algorithm," in Heliyon, vol. 6, no. 8, 2020, https://doi.org/10.1016/j.heliyon.2020.e04648.
N. Derbel, J. Ghommam, and Q. Zhu, Applications of Sliding Mode Control. Singapore: Springer, 2017, https://doi.org/10.1007/978-981-10-2374-3.
L. Fridman and A. Poznyak, "Robust Output LQ Optimal Control via Integral Sliding Modes," in IEEE Transactions on Automatic Control, vol. 56, no. 11, pp. 2699-2704, 2011, https://doi.org/10.1109/TAC.2011.2159420.
L. Wu, J. Liu, S. Vazquez, and S. K. Mazumder, "Sliding Mode Control in Power Converters and Drives: A Review," in IEEE/CAA Journal of Automatica Sinica, vol. 9, no. 3, pp. 392-406, 2022, https://doi.org/10.1109/JAS.2021.1004380.
C. A. Martínez-Fuentes, U. Pérez-Ventura, and L. Fridman, "Chattering analysis for Lipschitz continuous sliding-mode controllers," in International Journal of Robust and Nonlinear Control, vol. 31, no. 9, pp. 3779-3794, 2021, https://doi.org/10.1002/rnc.5239.
L. Qu, W. Qiao, and L. Qu, "Active-Disturbance-Rejection-Based Sliding-Mode Current Control for Permanent-Magnet Synchronous Motors," in IEEE Transactions on Power Electronics, vol. 36, no. 1, pp. 751-760, 2021, https://doi.org/10.1109/TPEL.2020.3003666.
X. Xiong, H. Chen, Y. Lou, Z. Liu, S. Kamal, and M. Yamamoto, "Implicit Discrete-Time Adaptive First-Order Sliding Mode Control With Predefined Convergence Time," in IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 68, no. 12, pp. 3562-3566, 2021, https://doi.org/10.1109/TCSII.2021.3070435.
S. Chen, W. Huang, and Q. Liu, "A New Adaptive Robust Sliding Mode Control Approach for Nonlinear Singular Fractional-Order Systems," in Fractal and Fractional, vol. 6, no. 5, 2022, https://doi.org/10.3390/fractalfract6050253.
F. Shiravani, P. Alkorta, J. A. Cortajarena, and O. Barambones, "An Enhanced Sliding Mode Speed Control for Induction Motor Drives," in Actuators, vol. 11, no. 1, 2022, https://doi.org/10.3390/act11010018.
A. Chalanga et al., "Implementation of Super-Twisting Control: Super-Twisting and Higher-Order Sliding-Mode Observer-Based Approaches," in IEEE Transactions on Industrial Electronics, vol. 63, no. 6, pp. 3677-3685, 2016, https://doi.org/10.1109/TIE.2016.2523913.
R. Seeber and M. Reichhartinger, "Conditioned Super-Twisting Algorithm for Systems with Saturated Control Action," in Automatica, vol. 116, p. 108921, 2020, https://doi.org/10.1016/j.automatica.2020.108921.
S. Ding, Q. Hou, and H. Wang, "Disturbance-Observer-Based Second-Order Sliding Mode Controller for Speed Control of PMSM Drives," in IEEE Transactions on Energy Conversion, vol. 38, no. 1, pp. 100-110, 2023, https://doi.org/10.1109/TEC.2022.3188630.
B. Wang, T. Wang, Y. Yu, and D. Xu, "Second-Order Terminal Sliding-Mode Speed Controller for Induction Motor Drives With Nonlinear Control Gain," in IEEE Transactions on Industrial Electronics, vol. 70, no. 11, pp. 10923-10934, 2023, https://doi.org/10.1109/TIE.2022.3231248.
N. T. Pham, "Design of Novel STASOSM Controller for FOC Control of Dual Star Induction Motor Drives," in International Journal of Robotics and Control Systems, vol. 4, no. 3, pp. 1059-1074, 2024, https://doi.org/10.31763/ijrcs.v4i3.1443.
A. Nurettin and N. İnanç, "High-Performance Induction Motor Speed Control Using a Robust Hybrid Controller With a Supertwisting Sliding Mode Load Disturbance Observer," in IEEE Transactions on Industrial Electronics, vol. 70, no. 8, pp. 7743-7752, 2023, https://doi.org/10.1109/TIE.2022.3222625.
N. T. Pham and T. D. Le, "A Novel FOC Vector Control Structure Using RBF Tuning PI and Sliding Mode for SPIM Drives," in International Journal of Intelligent Engineering Systems, vol. 13, no. 5, pp. 429-440, 2020, https://doi.org/10.22266/ijies2020.1031.38.
Z. Kang, X. Lin, Z. Liu, X. Shen, Y. Gao, and J. Liu, "Adaptive Generalized Super-Twisting Sliding Mode Control for PMSM Drives," in IEEE Transactions on Energy Conversion, vol. 41, no. 1, pp. 148-159, 2026, https://doi.org/10.1109/TEC.2025.3590203.
N. T. Pham, "An Improved BS_NAHOSM Hybrid Control Strategy for FOC of Dual Star Induction Motor Drives," in Periodica Polytechnica Electrical Engineering and Computer Science, vol. 69, no. 3, pp. 226-235, 2025, https://doi.org/10.3311/PPee.37384.
A. Ammar, O. Belaroussi, A. Zemmit, H. Said, and N. Belmadani, "Super-Twisting MRAS Observer-Based Non-linear Direct Flux and Torque Control for Induction Motor Drives," in Power Electronics and Drives, vol. 9, no. 2, pp. 55-66, 2024, https://doi.org/10.2478/pead-2024-0024.
M. Hu, H. Ahn, and K. You, "Speed Tracking of SPMSM via Super-Twisting Logarithmic Fast Terminal Sliding-Mode Control," in IEEE Access, vol. 11, pp. 91904-91912, 2023, https://doi.org/10.1109/ACCESS.2023.3308156.
W. Wang, Y. Ye, X. Chen, and Y. Yuan, "Adaptive High-Order Sliding-Mode Low-Speed Control With RBF Neural Network Nonlinear Disturbance Observer for PMSM Drive System," in IEEE Transactions on Power Electronics, vol. 40, no. 8, pp. 10865-10876, 2025, https://doi.org/10.1109/TPEL.2025.3559890.
H. Ríos, R. Franco, A. F. de Loza, and D. Efimov, "A High-Order Sliding-Mode Adaptive Observer for Uncertain Nonlinear Systems," in IEEE Transactions on Automatic Control, vol. 68, no. 1, pp. 408-415, 2023, https://doi.org/10.1109/TAC.2021.3139308.
I. M. Mehedi, N. Saad, M. A. Magzoub, U. M. Al-Saggaf, and A. H. Milyani, "Simulation Analysis and Experimental Evaluation of Improved Field-Oriented Controlled Induction Motors Incorporating Intelligent Controllers," in IEEE Access, vol. 10, pp. 18380-18394, 2022, https://doi.org/10.1109/ACCESS.2022.3150360.
L. Yi et al., "Intelligent detection of stator and rotor faults of induction motor based on improved backstepping sliding mode observer," in International Journal of Dynamics and Control, vol. 11, pp. 666-679, 2023, https://doi.org/10.1007/s40435-022-01010-7.
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Quang Huy Le, Ngoc Thuy Pham
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
This journal is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
