Event-Triggered Control for Course Tracking of Underactuated Ships Considering Actuator Faults

Shengda Ding

doi:10.54097/ed4wbr29

Authors

Shengda Ding School of Navigation, Shandong Jiaotong University, Shandong 264200 China

DOI:

https://doi.org/10.54097/ed4wbr29

Keywords:

Event-Triggered Control, Adaptive Control, Neural Network, Input Saturation

Abstract

Addressing the course-keeping control problem of underactuated surface vessels subject to strong unknown environmental disturbances and asymmetric actuator saturation, this paper proposes an event-triggered (ETC) adaptive control scheme. A Radial Basis Function (RBF) neural network is constructed to approximate external disturbances and model uncertainties. To handle the impact of non-smooth asymmetric saturation nonlinearities, a continuously differentiable model based on the Gaussian error function is employed. An ETC is introduced to significantly reduce the frequency of controller updates, and a trajectory tracker is designed utilizing the backstepping method. The stability of the closed-loop system is theoretically proven via Lyapunov stability analysis. The control algorithm is simulated within the MATLAB environment to evaluate tracking performance. Simulation results demonstrate that the controller achieves precise and stable tracking, with the number of updates reduced by 1,056—amounting to a 44.0% reduction in communication resource utilization. This research provides a theoretical reference for the trajectory tracking of underactuated vessels under event-triggered mechanisms and asymmetric actuator constraints, with potential for further application in practical engineering.

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