Adaptive sliding mode attitude control of 2-degrees-of-freedom helicopter system with actuator saturation and disturbances

Li, Ruobing; Lei, Changyi; Shi, Baiyang; Zhu, Quanmin; Yue, Xicai

Abstract

The modelling uncertainties, external disturbance and actuator saturation issues will degrade the performance and even the safety of flight. To improve control performance, this study proposes an adaptive U-model based double sliding control (UDSMC) algorithm combined with a radial basis function neural network (RBFNN) for a nonlinear two-degrees-of-freedom (2-DOF) helicopter system. Firstly, the adaptive RBFNN is designed to approximate the system dynamics with unknown uncertainties. Furthermore, two adaptive laws are designed to deal with unknown external disturbances and actuator saturation errors. The global stability of the proposed helicopter control system is rigorously guaranteed by the Lyapunov stability analysis, realizing precise attitude tracking control. Finally, the comparative experiments with conventional SMC and adaptive SMC algorithms conducted on the Quanser Aero2 platform demonstrate the effectiveness and feasibility of the proposed 2-DOF helicopter control algorithm.

• Journal Article Type: Article
• Acceptance Date: Oct 19, 2023
• Online Publication Date: Nov 13, 2023
• Deposit Date: Jan 23, 2024
• Publicly Available Date: Nov 17, 2024
• Journal: JVC/Journal of Vibration and Control
• Print ISSN: 1077-5463
• Electronic ISSN: 1741-2986
• Publisher: SAGE Publications
• Peer Reviewed: Peer Reviewed
• Volume: 30
• Issue: 19-20
• Pages: 4572-4590
• DOI: https://doi.org/10.1177/10775463231212530
• Keywords: Mechanical Engineering, Mechanics of Materials, Aerospace Engineering, Automotive Engineering, General Materials Science
• Public URL: https://uwe-repository.worktribe.com/output/11462620