Adaptive Fast Terminal sliding mode Control for Inverted Pendulum on Cart
Main Article Content
Abstract
This paper presents an innovative control strategy, the Adaptive Fast Terminal Sliding Mode Control (AFTSMC), designed for the stability control of an inverted pendulum on a cart. The proposed controller aims to stabilize the system within a finite time, leveraging the advantages of fast terminal sliding mode techniques. The system’s dynamic model is employed to derive the controller, utilizing an adaptive approach to accommodate uncertainties and disturbances. Simulations are conducted to validate the proposed AFTSMC, comparing its performance with an Adaptive Sliding Mode Controller under various scenarios. The results demonstrate the efficacy of the AFTSMC in achieving stable and precise control, making it a promising solution for the challenging dynamics of inverted pendulum systems.
Keywords
Sliding mode control, Adaptive fast terminal sliding mode control, Inverted pendulum.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
References
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[21] Jinkun Liu and Xinhua Wang, Adaptive sliding mode control for mechanical systems, in Advanced sliding mode control for mechanical systems, 1st ed. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011, pp. 117-135. https://doi.org/10.1007/978-3-642-20907-9
[2] José Guadalupe Romero, Alejandro Donaire, and Romeo Ortega. Robust energy shaping control of mechanical systems, Systems & Control Letters, 62(9):770-780, 2013. https://doi.org/10.1016/j.sysconle.2013.05.011
[3] Xin Xin, Seiji Tanaka, Jinhua She, and Taiga Yamasaki, New analytical results of energy-based swing-up control for the pendubot, International Journal of Non-Linear Mechanics, 52:110-118, 2013. https://doi.org/10.1016/j.ijnonlinmec.2013.02.003
[4] B. Salamat and A. M. Tonello, A swash mass pendulum with passivity-based control, IEEE Robotics and Automation Letters, vol. 6, no. 1, pp. 199-206, Jan. 2021. https://doi.org/10.1109/LRA.2020.3037861
[5] Y. Zhang, S. Li, J. Zou and A. H. Khan, A passivitybased approach for kinematic control of manipulators with constraints, IEEE Transactions on Industrial Informatics, vol. 16, no. 5, pp. 3029-3038, May 2020. https://doi.org/10.1109/TII.2019.2908442
[6] Rigatos G, Busawon K, Pomares J, Abbaszadeh M. Nonlinear optimal control for the wheeled inverted pendulum system, Robotica. 2020; 38(1): pp. 29-47. https://doi.org/10.1017/S0263574719000456
[7] E. Susanto, A. Surya Wibowo and E. Ghiffary Rachman, Fuzzy swing up control and optimal state feedback stabilization for self-erecting inverted pendulum, IEEE Access, vol. 8, pp. 6496-6504, 2020. https://doi.org/10.1109/ACCESS.2019.2963399
[8] Borase, R. P., Maghade, D. K., Sondkar, S.Y. et al. A review of PID control, tuning methods and applications, Int. J. Dynam. Control 9, pp. 818-827 (2021). https://doi.org/10.1007/s40435-020-00665-4
[9] Indrazno Siradjuddin, Zakiyah Amalia, Budhy Setiawan, Ferdian Ronilaya, Erfan Rohadi, Awan Setiawan, Cahya Rahmad, and Supriatna Adhisuwignjo, Stabilising a cart inverted pendulum with an augmented pid control scheme, in MATEC Web of Conferences, vol 197, pp. 11013. EDP Sciences, 2018. https://doi.org/10.1051/matecconf/201819711013
[10] S. K. Valluru, M. Singh, M. Singh and V. Khattar, Experimental validation of PID and LQR control techniques for stabilization of cart inverted pendulum system, in 2018 3rd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT), Bangalore, India, 2018, pp. 708-712. https://doi.org/10.1109/RTEICT42901.2018.9012643 [11] R. Banerjee, N. Dey, U. Mondal and B. Hazra, Stabilization of double link inverted pendulum using LQR, in 2018 International Conference on Current Trends towards Converging Technologies (ICCTCT), Coimbatore, India, 2018, pp. 1-6. https://doi.org/10.1109/ICCTCT.2018.8550915
[12] Sondarangallage D. A. Sanjeewa & Manukid Parnichkun Control of rotary double inverted pendulum system using LQR sliding surface based sliding mode controller, Journal of Control and Decision, 9:1, 2022, pp. 89-101 https://doi.org/10.1080/23307706.2021.1914758
[13] S. Nakatani and H. Date, Swing up control of inverted pendulum on a cart with collision by monte carlo model predictive control, in 2019 58th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE), Hiroshima, Japan, 2019, pp. 1050-1055. https://doi.org/10.23919/SICE.2019.8859912
[14] R. Firmansyah and P. P. S. Saputra, Design of model predictive control to stabilize two-stage inverted pendulum, in 2020 Third International Conference on Vocational Education and Electrical Engineering (ICVEE), Surabaya, Indonesia, 2020, pp. 1-5 https://doi.org/10.1109/ICVEE50212.2020.9243211
[15] D. Liao-McPherson, T. Skibik, J. Leung, I. Kolmanovsky and M. M. Nicotra, An analysis of closed-loop stability for linear model predictive control based on time-distributed optimization, IEEE Transactions on Automatic Control, vol. 67, no. 5, pp. 2618-2625, May 2022 https://doi.org/10.1109/TAC.2021.3086295
[16] Saqib Irfan, Adeel Mehmood, Muhammad Tayyab Razzaq, Jamshed Iqbal, Advanced sliding mode control techniques for inverted pendulum: modelling and simulation, Engineering Science and Technology, an International Journal, vol. 21, no. 4, 2018, pp. 753-759, ISSN 2215-0986. https://doi.org/10.1016/j.jestch.2018.06.010
[17] J. Huang, M. Zhang, S. Ri, C. Xiong, Z. Li and Y. Kang, High-order disturbance-observer-based sliding mode control for mobile wheeled inverted pendulum systems, IEEE Transactions on Industrial Electronics, vol. 67, no. 3, pp. 2030-2041, March 2020. https://doi.org/10.1109/TIE.2019.2903778
[18] Wang, J., Zhu, P., He, B. et al. An adaptive neural sliding mode control with ESO for uncertain nonlinear systems, Int. J. Control Autom. Syst, vol. 19, pp. 687-697 (2021). https://doi.org/10.1007/s12555-019-0972-x
[19] J. P. Mishra, X. Yu, M. Jalili and Y. Feng, On fast terminal sliding-mode control design for higher order systems, in IECON 2016 - 42nd Annual Conference of the IEEE Industrial Electronics Society, Florence, Italy, 2016, pp. 252-257. https://doi.org/10.1109/IECON.2016.7792972
[20] Y. Pan, C. Yang, L. Pan and H. Yu, Integral sliding mode control: performance, modification, and improvement, IEEE Transactions on Industrial Informatics, vol. 14, no. 7, pp. 3087-3096, July 2018. https://doi.org/10.1109/TII.2017.2761389
[21] Jinkun Liu and Xinhua Wang, Adaptive sliding mode control for mechanical systems, in Advanced sliding mode control for mechanical systems, 1st ed. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011, pp. 117-135. https://doi.org/10.1007/978-3-642-20907-9