Reliable Intelligent Path Following Control for a Robotic Airship Against Sensor Faults

• Published in: IEEE/ASME transactions on mechatronics Vol. 24; no. 6; pp. 2572 - 2582
• Main Authors: Wang, Yueying, Zhou, Weixiang, Luo, Jun, Yan, Huaicheng, Pu, Huayan, Peng, Yan
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.12.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptive backstepping sliding mode control; Adaptive control; adaptive neuro-fuzzy inference system (ANFIS); Airships; Artificial neural networks; Atmospheric modeling; Backstepping; Computer simulation; Control stability; Control systems; Control systems design; Fuzzy logic; Fuzzy systems; Mathematical model; path following control; Robot control; Robot sensing systems; robotic airship; sensor faults; Sensors; Sliding mode control; Trajectory planning; Uncertainty
• ISSN: 1083-4435; 1941-014X
• DOI: 10.1109/TMECH.2019.2929224

This paper presents a reliable intelligent path following control method for a robotic airship subject to sensor faults. First, an adaptive backstepping sliding mode controller is designed based on the six degrees of freedom model of airship, where the backstepping technique is used to obtain the desired velocities, and the adaptive sliding mode method is adopted to deal with the unknown model uncertainties. The stabilization of the whole path following control system is studied based on Lyapunov stability theory. Specially, since the measured data in the airship control system are interrelated, a data-driven soft sensor based on adaptive neuro-fuzzy inference system is designed to detect and isolate the sensor fault. Based on the developed detection and isolation mechanism, the airship control system still work well in the presence of sensor fault. Finally, simulations are given to demonstrate the effectiveness of the proposed path following strategy.