Interdisciplinary Education Promotes Scientific Research Innovation: Take the Composite Control of the Permanent Magnet Synchronous Motor as an Example
Abstract
:1. Introduction
- In contrast to the traditional integer-order ultra-local model of the PMSM, the fractional-order ultra-local model is now being employed to more precisely represent the original complex system dynamics, thereby facilitating the development of a comprehensive controller design.
- To estimate the internal and external disturbances of this model, a novel fractional-order nonlinear extended state observer (FNESO) is proposed. To date, no other researcher has proposed this innovative approach. Although a fractional-order ESO was previously introduced in [36], it was primarily focused on constructing a fractional-order linear ESO for disturbance compensation, without fully addressing the complexities inherent in the model.
- This paper introduces a novel approach to control systems design, which incorporates the Lyapunov stability theory. Specifically, we put forward a fractional-order nonsingular terminal sliding mode control method in this study. The core of the controller is based on a new type of fractional-order sliding mode, which offers several advantages including enhanced robustness, rapid convergence, reduced chattering, and the prevention of singularities.
- The stability analysis of the closed-loop system, utilizing the proposed control method, is demonstrated through the application of the Lyapunov theorem and Mittag–Leffler theory. Additionally, a comparison of results has been conducted to validate the efficiency and distinct advantages of the proposed control approach.
2. Problem Description
3. Preliminaries
4. Control Strategies and Stability Analysis
5. Comparative Results
- Case I: speed response curves comparison.
- Case II: comparison of speed-tracking performance.
- Case III: comparing resistance to uncertainties and disturbances.
- Case IV: comparison of disturbance estimation.
- Case V: comparison of control signals.
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Li, Y.; Yan, Y.; Li, M.J. Does interdisciplinary research lead to higher faculty performance? Evidence from an accelerated research university in China. Sustainability 2022, 14, 13977. [Google Scholar] [CrossRef]
- John, H. Sustaining interdisciplinary education: Developing boundary crossing governance. High. Educ. Res. Dev. 2018, 37, 1424–1438. [Google Scholar]
- John, G.H.; Stephanie, S.; Alison, F.S.; Amal, D.A.; Michael, J.A.; Ayaz, A.; Dik, B.; John, V.B.; David, B.; Adam, B.; et al. Potential for chemistry in multidisciplinary, interdisciplinary, and transdisciplinary teaching activities in higher education. J. Chem. Educ. 2021, 98, 1124–1145. [Google Scholar]
- Sandra, B.; ElSayary, A. Driving transformation in higher education: Exploring the process and impact of educational innovations for sustainability through interdisciplinary studies. High. Educ. Q. 2024, e12529. [Google Scholar] [CrossRef]
- Van den Beemt, A.; MacLeod, M.; Van der Veen, J.; Van de Ven, A.; Van Baalen, S.; Klaassen, R.; Boon, M. Interdisciplinary engineering education: A review of vision, teaching, and support. J. Eng. Educ. 2020, 109, 508–555. [Google Scholar] [CrossRef]
- Turner, R.; Cotton, D.; Morrison, D.; Kneale, P. Embedding interdisciplinary learning into the first-year undergraduate curriculum: Drivers and barriers in a cross-institutional enhancement project. Teach. High. Educ. 2024, 29, 1092–1108. [Google Scholar] [CrossRef]
- Xie, F.; Xu, J.; Shen, M.; Zheng, Z. Current harmonic suppression strategy for permanent magnet synchronous motor based on small phase angle resonant controller. IET Electr. Power Appl. 2024, 8, 556–564. [Google Scholar] [CrossRef]
- Zhao, K.; Liu, W.; Zhou, R.; Dai, W.; Wu, S.; Qiu, P.; Yin, Y.; Jia, N.; Yi, J.; Huang, G. Model-free fast integral terminal sliding-mode control method based on improved fast terminal sliding-mode observer for PMSM with unknown disturbances. ISA Trans. 2023, 143, 572–581. [Google Scholar] [CrossRef]
- Wang, S.; Gan, H.; Luo, Y.; Luo, X.; Chen, Y. A Fractional-order ADRC architecture for a PMSM position servo system with improved disturbance rejection. Fractal Fract. 2024, 8, 54. [Google Scholar] [CrossRef]
- Xiong, J.; Fu, X. Extended two-state observer-based speed control for PMSM with uncertainties of control input gain and lumped disturbance. IEEE Trans. Ind. Electron. 2024, 71, 6172–6182. [Google Scholar] [CrossRef]
- Gao, P.; Zhang, G.; Ouyang, H.; Mei, L. An adaptive super twisting nonlinear Fractional-order PID sliding mode control of permanent magnet synchronous motor speed regulation system based on extended state observer. IEEE Access 2020, 8, 53498–53510. [Google Scholar] [CrossRef]
- Gao, P.; Pan, H. Model-free double Fractional-order integral sliding mode control for permanent magnet synchronous motor based electric mopeds drive system. IEICE Electron. Express 2023, 20, 20230178. [Google Scholar] [CrossRef]
- Abbes, A.; Ouannas, A.; Shawagfeh, N.; Jahanshahi, H. The Fractional-order discrete COVID-19 pandemic model: Stability and chaos. Nonlinear Dyn. 2023, 111, 965–983. [Google Scholar] [CrossRef] [PubMed]
- Dassios, I.; Kërçi, T.; Baleanu, D.; Milano, F. Fractional-order dynamical model for electricity markets. Math. Methods Appl. Sci. 2023, 46, 8349–8361. [Google Scholar] [CrossRef]
- Zheng, Z.; Cai, Z.; Su, G.; Huang, S.; Wang, W.; Zhang, Q.; Wang, Y. A new Fractional-order model for time-dependent damage of rock under true triaxial stresses. Int. J. Damage Mech. 2023, 32, 50–72. [Google Scholar] [CrossRef]
- Xue, W.; Li, Y.; Cang, S.; Jia, H.; Wang, Z. Chaotic behavior and circuit implementation of a Fractional-order permanent magnet synchronous motor model. J. Frankl. Inst. 2015, 352, 2887–2898. [Google Scholar] [CrossRef]
- Zhang, S.; Wang, C.; Zhang, H.; Ma, P.; Li, X. Dynamic analysis and bursting oscillation control of Fractional-order permanent magnet synchronous motor system. Chaos Solitons Fractals 2022, 156, 111809. [Google Scholar] [CrossRef]
- Sheng, Y.; Gan, J.; Guo, X. Predefined-time Fractional-order time-varying sliding mode control for arbitrary order systems with uncertain disturbances. ISA Trans. 2024, 146, 236–248. [Google Scholar] [CrossRef]
- Zhang, B.; Pi, Y.; Luo, Y. Fractional-order sliding-mode control based on parameters auto-tuning for velocity control of permanent magnet synchronous motor. ISA Trans. 2012, 51, 649–656. [Google Scholar] [CrossRef]
- Chu, Y.; Hou, S.; Wang, C.; Fei, J. Recurrent-neural-network-based Fractional-order sliding mode control for harmonic suppression of power grid. IEEE Trans. Ind. Inform. 2023, 19, 9979–9990. [Google Scholar] [CrossRef]
- El Ferik, S.; Al-Qahtani, F.M.; Saif, A.W.A.; Al-Dhaifallah, M. Robust FOSMC of quadrotor in the presence of slung load. ISA Trans. 2023, 139, 106–121. [Google Scholar] [CrossRef]
- Chávez-Vázquez, S.; Lavín-Delgado, J.E.; Gómez-Aguilar, J.F.; Razo-Hernández, J.R.; Etemad, S.; Rezapour, S. Trajectory tracking of Stanford robot manipulator by Fractional-order sliding mode control. Appl. Math. Model. 2023, 120, 436–462. [Google Scholar] [CrossRef]
- Fan, J.; Chen, S.; Wang, W.; Ji, Y.; Liu, N. Piecewise trajectory and angle constraint based Fractional-order sliding mode control. IEEE Trans. Aerosp. Electron. Syst. 2023, 59, 6782–6797. [Google Scholar] [CrossRef]
- Zhang, L.; Tao, R.; Zhang, Z.X.; Chien, Y.R.; Bai, J. PMSM non-singular fast terminal sliding mode control with disturbance compensation. Inf. Sci. 2023, 642, 119040. [Google Scholar] [CrossRef]
- Wang, C.; Liu, F.; Xu, J.; Pan, J. A SMC-based accurate and robust load speed control method for elastic servo system. IEEE Trans. Ind. Electron. 2023, 71, 2300–2308. [Google Scholar] [CrossRef]
- Tian, M.; Wang, B.; Yu, Y.; Dong, Q.; Xu, D. Adaptive active disturbance rejection control for uncertain current ripples suppression of PMSM Drives. IEEE Trans. Ind. Electron. 2023, 71, 2320–2331. [Google Scholar] [CrossRef]
- Wu, J.; Zhao, Y.; Kong, Y.; Liu, Q.; Zhang, L. Hierarchical non-singular terminal sliding mode control with finite-time disturbance observer for PMSM speed regulation system. IEEE Trans. Transp. Electrif. 2023. [Google Scholar] [CrossRef]
- Hou, Q.; Xu, S.; Zuo, Y.; Wang, H.; Sun, J.; Lee, C.H.; Ding, S. Enhanced active disturbance rejection control with measurement noise suppression for PMSM drives via augmented nonlinear extended state observer. IEEE Trans. Energy Convers. 2024, 39, 287–299. [Google Scholar] [CrossRef]
- Zhang, Y.; Wu, H.; Chien, Y.R.; Tang, J. Vector control of permanent magnet synchronous motor drive system based on new sliding mode control. IEICE Electron. Express 2023, 20, 20230263. [Google Scholar] [CrossRef]
- Gao, P.; Pan, H.; Zhu, Y. One new composite control based smooth nonlinear Fractional-order sliding mode algorithm and disturbance compensation for PMSM with parameter uncertainties. Adv. Mech. Eng. 2023, 15, 16878132231216858. [Google Scholar] [CrossRef]
- Ge, H.; Liu, Y. Composite Fractional-order sliding mode controller for PMSM drives based on GPIO. Meas. Control 2022, 55, 1134–1142. [Google Scholar] [CrossRef]
- Kang, J. Ultra-local model-free adaptive super-twisting nonsingular terminal sliding mode control for magnetic levitation system. IEEE Trans. Ind. Electron. 2023, 71, 5187–5194. [Google Scholar] [CrossRef]
- Wang, H.; Ghazally, I.; Tian, Y. Model-free Fractional-order sliding mode control for an active vehicle suspension system. Adv. Eng. Softw. 2018, 115, 452–461. [Google Scholar] [CrossRef]
- Wei, Y.; Young, H.; Wang, F.; Rodríguez, J. Generalized data-driven model-free predictive control for electrical drive systems. IEEE Trans. Ind. Electron. 2022, 70, 7642–7652. [Google Scholar] [CrossRef]
- He, D.; Wang, H.; Tian, Y.; Guo, Y. A Fractional-order ultra-local model-based adaptive neural network sliding mode control of n-DOF upper-limb exoskeleton with input deadzone. IEEE/CAA J. Autom. Sin. 2024, 11, 760–781. [Google Scholar] [CrossRef]
- Li, B.; Zhu, L.; Chen, Z. An improved active disturbance rejection control for bode’s ideal transfer function. IEEE Trans. Ind. Electron. 2024, 71, 7673–7683. [Google Scholar] [CrossRef]
- Jiang, J.; Zhang, H.; Jin, D.; Wang, A.; Liu, L. Disturbance observer based non-singular fast terminal sliding mode control of permanent magnet synchronous motors. J. Power Electron. 2024, 24, 249–257. [Google Scholar] [CrossRef]
- Zhang, Z.; Liu, X.; Yu, J.; Yu, H. Time-varying disturbance observer based improved sliding mode single-loop control of PMSM drives with a hybrid reaching law. IEEE Trans. Energy Convers. 2023, 38, 2539–2549. [Google Scholar] [CrossRef]
- Li, C.; Deng, W. Remarks on fractional derivatives. Appl. Math. Comput. 2007, 187, 777–784. [Google Scholar] [CrossRef]
- Yang, B.; Yu, T.; Shu, H.; Zhu, D.; An, N.; Sang, Y.; Jiang, L. Perturbation observer based Fractional-order sliding-mode controller for MPPT of grid-connected PV inverters: Design and real-time implementation. Control Eng. Pract. 2018, 79, 105–125. [Google Scholar] [CrossRef]
- Qian, D.; Li, C.; Agarwal, R.P.; Wong, P.J. Stability analysis of fractional differential system with Riemann-Liouville derivative. Math. Comput. Model. 2010, 52, 862–874. [Google Scholar] [CrossRef]
- Li, Y.; Chen, Y.; Podlubny, I. Stability of Fractional-order nonlinear dynamic systems: Lyapunov direct method and generalized Mittag-Leffler stability. Comput. Math. Appl. 2010, 59, 1810–1821. [Google Scholar] [CrossRef]
- Cuong, H.M.; Van Thai, N.; Van Trieu, P.; Dong, H.Q.; Nam, T.T.; Viet, T.X.; Nho, L.C. Nonsingular Fractional-order integral fast-terminal sliding mode control for underactuated shipboard cranes. J. Frankl. Inst. 2022, 359, 6587–6606. [Google Scholar] [CrossRef]
- Mermoud, M.; Camacho, N. Using general quadratic Lyapunov functions to prove Lyapunov uniform stability for Fractional-order systems. Commun. Nonlinear Sci. Numer. Simul. 2015, 22, 650–659. [Google Scholar] [CrossRef]
- Fliess, M.; Cédric, J. Model-free control. Int. J. Control 2013, 86, 2228–2252. [Google Scholar] [CrossRef]
- Fliess, M.; Cédric, J. Intelligent PID controllers. In Proceedings of the 2008 16th Mediterranean Conference on Control and Automation, Ajaccio, France, 25–27 June 2008. [Google Scholar]
- Yang, H.; Guo, M.; Xia, Y.; Sun, Z. Dual closed-loop tracking control for wheeled mobile robots via active disturbance rejection control and model predictive control. Int. J. Robust Nonlinear Control 2020, 30, 80–99. [Google Scholar] [CrossRef]
- Gao, P.; Zhang, G.; Lv, X. Model-free control using improved smoothing extended state observer and super-twisting nonlinear sliding mode control for PMSM drives. Energies 2021, 14, 922. [Google Scholar] [CrossRef]
- Wang, Y.; Chen, J.; Yan, F.; Zhu, K.; Chen, B. Adaptive super-twisting Fractional-order nonsingular terminal sliding mode control of cable-driven manipulators. ISA Trans. 2019, 86, 163–180. [Google Scholar] [CrossRef] [PubMed]
- Wang, Y.; Li, S.; Wang, D.; Ju, F.; Chen, B.; Wu, H. Adaptive time-delay control for cable-driven manipulators with enhanced nonsingular fast terminal sliding mode. IEEE Trans. Ind. Electron. 2020, 68, 2356–2367. [Google Scholar] [CrossRef]
- Lv, X.; Zhang, G.; Bai, Z.; Zhou, X.; Shi, Z.; Zhu, M. Adaptive neural network global Fractional order fast terminal sliding mode model-free intelligent PID control for hypersonic vehicle’s ground thermal environment. Aerospace 2023, 10, 777. [Google Scholar] [CrossRef]
- Zhang, G.; Gao, L.; Yang, H.; Mei, L. A novel method of model predictive control on permanent magnet synchronous machine with Laguerre functions. Alex. Eng. J. 2021, 60, 5485–5494. [Google Scholar] [CrossRef]
- Zhang, Z.; Yang, X.; Wang, W.; Chen, K.; Cheung, N.C.; Pan, J. Enhanced sliding mode control for PMSM speed drive systems using a novel adaptive sliding mode reaching law based on exponential function. IEEE Trans. Ind. Electron. 2024, 71, 11978–11988. [Google Scholar] [CrossRef]
4 | 0.958 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Gao, P.; Fang, L.; Pan, H. Interdisciplinary Education Promotes Scientific Research Innovation: Take the Composite Control of the Permanent Magnet Synchronous Motor as an Example. Mathematics 2024, 12, 2602. https://doi.org/10.3390/math12162602
Gao P, Fang L, Pan H. Interdisciplinary Education Promotes Scientific Research Innovation: Take the Composite Control of the Permanent Magnet Synchronous Motor as an Example. Mathematics. 2024; 12(16):2602. https://doi.org/10.3390/math12162602
Chicago/Turabian StyleGao, Peng, Liandi Fang, and Huihui Pan. 2024. "Interdisciplinary Education Promotes Scientific Research Innovation: Take the Composite Control of the Permanent Magnet Synchronous Motor as an Example" Mathematics 12, no. 16: 2602. https://doi.org/10.3390/math12162602