Adaptive Neural Control for an Uncertain 2-DOF Helicopter System with Unknown Control Direction and Actuator Faults

Bing Wu, Jiale Wu, Weitian He, Guojian Tang and Zhijia Zhao ()
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Bing Wu: College of Aerospace Science and Engineering, National University of Defence Technology, Changsha 410073, China
Jiale Wu: School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, China
Weitian He: School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, China
Guojian Tang: College of Aerospace Science and Engineering, National University of Defence Technology, Changsha 410073, China
Zhijia Zhao: School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, China

Mathematics, 2022, vol. 10, issue 22, 1-14

Abstract: In accordance with the rapid development of smart devices and technology, unmanned aerial vehicles (UAVs) have been developed rapidly. The two-degree-of-freedom helicopter system is a typical UAV that is susceptible to uncertainty, unknown control direction and actuator faults. Hence, a novel adaptive neural network (NN), fault-tolerant control scheme is proposed in this paper. Firstly, to compensate for the uncertainty, a radial-basis NN was developed to approximate the uncertain, unknown continuous function in the controlled system, and a novel weight-adaptive approach is proposed to save on computational cost. Secondly, a class of Nussbaum functions was chosen to solve the unknown-control-direction issue to prevent the effect of an unknown sign for the control coefficient. Subsequently, in response to the actuator faults, an adaptive parameter was designed to compensate for the performance loss of the actuators. Through rigorous Lyapunov analyses, the designed control scheme was proven to enable the states of the closed-loop system to be semi-globally uniformly bounded and the controlled system to be stable. Finally, we conducted a numerical simulation on Matlab to further verify the validity of the proposed scheme.

Keywords: adaptive NN control; uncertainty; unknown control direction; fault-tolerant control (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
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