Resilient Tracking Control for Unmanned Helicopter Under Variable Disturbance and Input Perturbation

• Published in: International journal of control, automation, and systems Vol. 20; no. 1; pp. 147 - 159
• Main Authors: Chen, Linbo, Li, Tao, Mao, Zehui, Fei, Shumin
• Format: Journal Article
• Language: English
• Published: Bucheon / Seoul Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers 01.01.2022; Springer Nature B.V; 제어·로봇·시스템학회
• Subjects: Closed loops; Control; Control methods; Control systems design; Control theory; Disturbance observers; Engineering; Feedback control; Feedforward control; Flapping; H-infinity control; Helicopter control; Linear matrix inequalities; Mathematical analysis; Mechatronics; Optimal control; Performance indices; Perturbation; Regular Papers; Robotics; Robust control; State observers; Stochastic processes; Tracking control; Unmanned helicopters; 제어계측공학; Backstepping control; disturbance observer-based control (DOBC); stochastic perturbation; unmanned aerial helicopter (UAH); resilient tracking control
• ISSN: 1598-6446; 2005-4092
• DOI: 10.1007/s12555-020-0590-7

In this work, by utilizing a disturbance observer-based control (DOBC) method, the resilient tracking control is studied for the unmanned aerial helicopter (UAH) with paramteter uncertainty, multiple disturbances, and input perturbation. Firstly, a state observer and two disturbance observers are respectively constructed to estimate the unmeasurable flapping motion states and outside disturbances, which are further utilized to design the feedforward controller. Secondly, by considering stochastic perturbation, a resilient feedback controller is proposed and an overall closed-loop error system is established. Thirdly, based on stochastic control theory and robust control method, a sufficient condition is obtained to guarantee the asymptotical stability and H∞ performance index for the closed-loop error system. Furthermore, the observer gains and controller one can be jointly checked by solving the derived linear matrix inequality (LMI). Finally, some simulations are presented to verify the effectiveness of the derived control method.