Practical Predefined-Time Formation Tracking of MASVs With Lumped Uncertainties via Estimator-Based Adaptive Fuzzy Control Algorithm
Shuang Wang, Tao Han, Bo Han Xiao, Xisheng Zhan, Huaicheng Yan · IEEE Transactions on Vehicular Technology · 2025
This article investigates the problem of practical predefined-time formation tracking for multiple autonomous surface vehicles facing the case of lumped uncertainties (namely, model uncertainties, external disturbances, and actuator failures). An estimator-based adaptive fuzzy control algorithm is designed to handle this complex problem, comprising two integral components: 1) a predefined-time distributed estimator and 2) an adaptive fuzzy formation tracking controller. The distributed estimator is designed to accurately estimate the target state within a predefined time. By utilizing filtering techniques to define the filtered errors, and combining fuzzy logic systems with adaptive compensation methods, an adaptive fuzzy controller is developed to achieve the time-varying formation tracking task. Sufficient conditions for achieving practical predefined-time convergence of the tracking errors are derived using Lyapunov stability analysis. Finally, numerical simulations involving multiple Cyber-Ships II are conducted to validate the primary results.