Model predictive control scheme for an inverted pendulum with disturbance

219 views

Authors

  • Nguyen Thanh Long (Corresponding Author) Hung Yen University of Technology and Education
  • Phan Xuan Minh Hanoi University of Science and Technology
  • Dao Phuong Nam Hanoi University of Science and Technology

DOI:

https://doi.org/10.54939/1859-1043.j.mst.86.2023.3-11

Keywords:

Perturbed Inverted Pendulum (IP); Model predictive control (MPC); Linear matrix inequalities (LMIs); Optimization; Stability.

Abstract

 The development of model predictive control (MPC) is difficult to establish predictive model under the influence of external disturbance. Moreover, the changing of optimization solutions after each computation step implies the stability effectiveness of the closed system is hard to satisfy although it can be guaranteed in each optimization problem at time instant. This paper presents a control design involving a MPC approach for the nominal discrete time system after eliminating external disturbance and the addition of handling external disturbance. In order to study the stability of MPC strategy, the optimization problem is established at each time instant satisfying linear matrix inequalities (LMIs) to achieve the comparison between Lyapunov function candidates at the consecutive sampling times. Simulation studies for a perturbed Inverted Pendulum (IP) are implemented to demonstrate the effectiveness of the proposed control scheme.   

References

[1]. Hu, X., Wei, X., Zhang, H., Han, J., Liu, X. “Robust adaptive tracking control for a class of mechanical systems with unknown disturbances under actuator saturation,” International Journal of Robust and Nonlinear Control 29, 1893–1908, (2019). DOI: https://doi.org/10.1002/rnc.4465

[2]. Boyd, S., Boyd, S.P., Vandenberghe, L., “Convex optimizations,”. Cambridge university press

[3]. Irfan, S., Mehmood, A., Razzaq, M.T., Iqbal, J., 2018. “Advanced sliding mode control techniques for inverted pendulum: Modelling and simulation,” International Journal of Engineering science and technology, 21, 753–759, (2004). DOI: https://doi.org/10.1016/j.jestch.2018.06.010

[4]. Su, X., Xia, F., Liu, J., Wu, L., “Event-triggered fuzzy control of nonlinear systems with its application to inverted pendulum systems,” Automatica 94, 236–248, (2018). DOI: https://doi.org/10.1016/j.automatica.2018.04.025

[5]. Baocang Ding, Hongguang Pan,“Output feedback robust MPC with one free control move for the linear polytopic uncertain system with bounded disturbance,” Automatica, Vol. 50, pp. 2929-2935, (2014). DOI: https://doi.org/10.1016/j.automatica.2014.10.021

[6]. Zhongqi Sun, Li Dai, Kun Liu, Yuanqing Xia, Karl Henrik Johansson,“Robust MPC for tracking constrained unicycle robots with additive disturbances,” Automatica, Volume. 90, pp. 172-184, 2018. DOI: https://doi.org/10.1016/j.automatica.2017.12.048

[7]. Long, Y., & Xie, L. “Unconstrained tracking MPC for continuous-time nonlinear systems,” Automatica, 129, 109680, (2021). DOI: https://doi.org/10.1016/j.automatica.2021.109680

[8]. Zhang, K., Sun, Q., & Shi, Y. “Trajectory tracking control of autonomous ground vehicles using adaptive learning MPC,” IEEE Transactions on Neural Networks and Learning Systems, (2021). DOI: https://doi.org/10.1109/TNNLS.2020.3048305

[9]. Kang, Yu, Tao Wang, Pengfei Li, Zhenyi Xu, and Yun-Bo Zhao. "Compound Event-Triggered Distributed MPC for Coupled Nonlinear Systems," IEEE Transactions on Cybernetics (2022). DOI: https://doi.org/10.1109/TCYB.2022.3159343

[10]. Gritli, H. “Robust master-slave synchronization of chaos in a one-sided 1-dof impact mechanical oscillator subject to parametric uncertainties and disturbances,” Mechanism and Machine Theory 142, 103610 (2019). DOI: https://doi.org/10.1016/j.mechmachtheory.2019.103610

Published

28-04-2023

How to Cite

Nguyễn Thành, L., M. Phan Xuân, and N. Đào Phương. “Model Predictive Control Scheme for an Inverted Pendulum With Disturbance”. Journal of Military Science and Technology, vol. 86, no. 86, Apr. 2023, pp. 3-11, doi:10.54939/1859-1043.j.mst.86.2023.3-11.

Issue

Section

Research Articles

Categories