A novel nonlinear resilient control for a quadrotor UAV via backstepping control and nonlinear disturbance observer
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This study proposes a novel nonlinear resilient trajectory control for a quadrotor unmanned aerial vehicle (UAV) using backstepping control and nonlinear disturbance observer. First, a nonlinear dynamic model for the quadrotor UAV that considers external disturbances from wind model uncertainties is developed. A nonlinear disturbance observer is then constructed separately from the controller to estimate the external disturbances and compensate for the negative effects of the disturbances. Based on the estimates from the given observer, a nominal nonlinear backstepping trajectory-tracking position controller is designed to stabilize the subsystems step by step until the ultimate control law is obtained. An extra term is added to the nominal controller to address the problem of actuator effectiveness loss and to ensure system resilience. The stability of the resilient controller is analyzed using Lyapunov stability theory. Simulation results are presented to demonstrate the effectiveness and robustness of the proposed nonlinear resilient controller.
KeywordsQuadrotor UAV Nonlinear disturbance observer Resilient control Disturbance compensation Backstepping controller
The project was supported by the Aeronautics Science Foundation of China (2014ZC52033) and the National Natural Science Foundation of China (61533009, 61374130, 61473146), a project funded by the Priority Academic Programme Development of Jiangsu Higher Education Institutions.
- 4.Mokhtari, A., Benallegue, A., Orlov, Y.: Exact linearization and sliding mode observer for a quadrotor unmanned aerial vehicle. Int. J. Robot. Autom. 21(1), 39–49 (2006)Google Scholar
- 7.Madani, T., Benallegue, A.: Backstepping sliding mode control applied to a miniature quadrotor flying robot. In: IEEE Industrial Electronics, IECON 2006-32nd annual conference on. IEEE, pp. 700–705 (2006)Google Scholar
- 8.Rong, X., Umit, O.: Sliding mode control of a quadrotor helicopter. In: Proceedings of the 45th IEEE conference on decision and control, pp. 4957–4962 (2006)Google Scholar
- 14.Pan, Y., Yu, H.: Composite learning from adaptive dynamic surface control. Automatic Control IEEE Trans. doi: 10.1109/TAC.2015.2495232 (2015)
- 18.Xu, B., Yang, C., Pan, Y.: Global neural dynamic surface tracking control of strict-feedback systems with application to hypersonic flight vehicle. IEEE Trans. Neural Netw. Learn. Syst. 26(10), 2563–2575 (2015)Google Scholar
- 19.Lee, T.: Robust adaptive attitude tracking on with an application to a quadrotor UAV. Control Syst. Technol. IEEE Trans. 21(5), 1924–1930 (2013)Google Scholar
- 21.Chamseddine, A., Theilliol, D., Zhang, Y.M.: Active fault tolerant control system design with trajectory replanning against actuator faults and saturation: Application to a quadrotor unmanned aerial vehicle. Int. J. Adapt. Control Signal Process. 29(1), 1–23 (2014)MathSciNetCrossRefMATHGoogle Scholar