RBFNN-Based Adaptive Fixed-Time Sliding Mode Tracking Control for Coaxial Hybrid Aerial–Underwater Vehicles Under Multivariant Ocean Disturbances

• DOI: 10.3390/drones8120745
• Publication Date: 2024-12-10T16:17:20Z
• Authors: Mingqing Lu; Wei Yang; Zhenyu Xiong; Fei Liao; Shichong Wu; Yumin Su; Wenhua Wu
• Keywords: Coaxial; Tracking (education); Mode (computer interface)

In this study, the design of an adaptive neural network-based fixed-time control system for a novel coaxial trans-domain hybrid aerial–underwater vehicle (HAUV) is investigated. A radial basis function network (RBFNN) approximation strategy-based terminal sliding mode (AFTSMC) scheme proposed to solve problems dynamic nonlinearity, model parameter perturbation, and multiple external disturbances HAUV trans-media motion. complete six-degrees-of-freedom continuous water–air cross-domain first established based on hyperbolic tangent transition function, and, subsequently, basic framework FTSMC, fast-convergence controller designed track target position attitude signals. To reduce dependence precise parameters, RBFNN approximator integrated into online identification aggregate uncertainties HAUV, such as nonlinear unmodeled dynamics disturbances. At same time, technique used approximate upper bound robust switching term gain in controller, which further offsets estimation error effectively attenuates chattering effect. Based Lyapunov stability theory, it proven that tracking can converge fixed time. The effectiveness superiority strategy are verified by several sets simulation results obtained under typical working conditions.