Abstract
This paper shows solicitude for the path following control issues of underactuated unmanned surface vehicles subject to unknown external disturbances, deviation of vessel model parameters and actuator saturation. Initially, an improved adaptive integral line-of-sight (IALOS) guidance law is introduced to estimate the sideslip angle, which helps to promote the precision of path following. Furthermore, a finite-time convergent disturbance observer is utilized to size up time-varying disturbances and the single-parameter neural network strategy is utilized to reduce the impact of model deviation. Meanwhile, by introducing a finite-time auxiliary dynamic system to improve the impact of actuator saturation (input saturation), the higher-order tracking differentiator (TDS) is introduced into the backstepping controller for reducing the number of derivations. It is shown that all error signals of the control system, employing Lyapunov stability theory, are uniformly ultimately bounded. Finally, the validity of the put forward scheme is validated by numerical simulations.
Highlights
Following Control Strategy for College of Marine Electrical Engineering, Dalian Maritime University, Dalian 116026, China; Key Laboratory of Technology and System for Intelligent Ships of Liaoning Province, Dalian 116026, China
For the sake of handling the issue of underactuated vehicle path following with uncertainty and input saturation, an improved LOS (ILOS) guidance method is proposed in Paper [13]
Based on an extended state observer (ESO), Paper [15] proposes an ESO LOS (ELOS) guidance method to handle the issue of time-varying sideslip angle and to improve the path following effect of underactuated unmanned vehicles when drift angle changes
Summary
In the last few years, the unmanned surface vehicle (USV) as an intelligent offshore platform facility has appealed to researchers from many fields [1–4] because of its small volume and fast speed. For the sake of handling the issue of underactuated vehicle path following with uncertainty and input saturation, an improved LOS (ILOS) guidance method is proposed in Paper [13]. LOS (PLOS) guidance method, which effectively reduces the influence of sideslip angle and obtains a more accurate guidance control law, is proposed in Paper [14]. Based on an extended state observer (ESO), Paper [15] proposes an ESO LOS (ELOS) guidance method to handle the issue of time-varying sideslip angle and to improve the path following effect of underactuated unmanned vehicles when drift angle changes. Paper [16] puts forward an IALOS guidance law to effectively improve the path following effect of USVs when sideslip angle and ocean current are time-varying. A path following control policy is designed by applying a singleparameter neural network, a finite-time auxiliary dynamic system, a higher-order tracking differentiator and a finite-time disturbance observer.
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