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Disturbance Observer-based LQR Tracking Control for Unmanned Autonomous Helicopter Slung-load System

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  • Control Theory and Applications
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Abstract

This work investigates the optimal tracking control for unmanned autonomous helicopter (UAH) slung-load system under external disturbance. Firstly, the linearized UAH slung-load system model is obtained by using the small perturbation linearization method, in which parameter uncertainty and disturbance are considered. Secondly, the control objective is described via a reference model, and the tracking controller is designed for the UAH slung-load system by using the reference model control approach, disturbance observer based-control (DOBC) scheme, and LQR control method. Thirdly, under the proposed tracking controller, the stability of the closed-loop system is analyzed on the basis of Lyapunov stability theory and linear matrix inequality (LMI) technique. Finally, some simulations and comparisons are presented to illustrate the proposed control method.

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Funding

This work was supported in part by the National Natural Science Foundation of China under Grant (U2013201, 62073164); in part by the Key R & D projects (Social Development) in Jiangsu Province of China under Grant BE2020704; in part by the Aeronautical Science Foundation of China under Grant 20200007052001.

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Authors and Affiliations

  1. School of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, China

    Lijun Liu, Mou Chen & Tao Li

Authors
  1. Lijun Liu
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  2. Mou Chen
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  3. Tao Li
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Corresponding author

Correspondence to Mou Chen.

Additional information

Lijun Liu received his M.S. degree at the College of Mathematics and Information Science, Guangxi University, Nanning in 2017. He is currently pursuing a Ph.D. degree in control theory and control engineering from the College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing. His Current research interests include include nonlinear system control and flight control.

Mou Chen is currently a Full Professor with the College of Automation Engineering, Nanjing University of Aeronautics and Astronautics. He was an Academic Visitor with the Department of Aeronautical and Automotive Engineering, Lough-borough University, U.K., from 2007 to 2008. From 2008 to 2009, he was a Research Fellow with the Department of Electrical and Computer Engineering, National University of Singapore. He was a Senior Academic Visitor with the School of Electrical and Electronic Engineering, University of Adelaide, Australia, in 2014. His research interests include nonlinear system control, intelligent control, and flight control.

Tao Li received his Ph.D. degree in engineering from Southeast University in 2008 and was a postdoctoral research fellow at the School of Instrument Science and Engineering of Southeast University during year 2008 and 2011, China. He has been a visiting scholar at Control System Center of Manchester University from year 2016 to 2017, UK. He is currently an associate professor at School of Automation Engineering, Nanjing University of Aeronautics and Astronautics in China. His current research interests include neural networks, time-delay systems, networked control systems, etc.

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Liu, L., Chen, M. & Li, T. Disturbance Observer-based LQR Tracking Control for Unmanned Autonomous Helicopter Slung-load System. Int. J. Control Autom. Syst. 20, 1166–1178 (2022). https://doi.org/10.1007/s12555-020-0514-6

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