FT-ILOS-Based Adaptive Fuzzy Path Following of USVs Under Input Saturation via Parallel-Self-Triggered Approach
Guibing Zhu, Junhui Li, Yong Ma, Songlin Hu
Abstract
In this article, we investigate a finite-time integral-line-of-sight (FT-ILOS)-based path following problem for the 4-degrees-of-freedom (4DOF) unmanned surface vehicles (USVs), where several practical factors, such as input saturations, uncertain dynamics, and environmental disturbances, are involved in the control design. To address input saturations, a dead-zone operator-based model is employed to replace hard-limited nonsmooth actuator saturation nonlinearity. To solve the control design problem caused by the under-actuated issue, a novel FT-ILOS guidance scheme is developed. Furthermore, an FT-ILOS-based adaptive fuzzy control solution is developed, in which a virtual parameter learning-based adaptive fuzzy approach is utilized to resolve the influence of the lumped uncertainty including uncertain dynamics and environmental disturbances. To reduce data transmission in the controller–actuator channel, an innovative parallel-self-triggered mechanism is structured. Thereby, an FT-ILOS-based parallel-self-triggered adaptive fuzzy control scheme is developed for the 4DOF USVs. Results show that all errors in the closed-loop system of 4DOF USVs are proven to be bounded, and the position error can converge to a small residual set within a finite time. Finally, the superiority of the developed control scheme is verified through simulation and comparison results.