Redirigiendo al acceso original de articulo en 17 segundos...
Inicio  /  Applied Sciences  /  Vol: 12 Par: 5 (2022)  /  Artículo
ARTÍCULO
TITULO

Robust Adaptive Path Following Control Strategy for Underactuated Unmanned Surface Vehicles with Model Deviation and Actuator Saturation

Yunsheng Fan    
Xinpeng Zou    
Guofeng Wang and Dongdong Mu    

Resumen

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.

 Artículos similares

       
 
Rong Li, Zhengliang Yang, Gaowei Yan, Long Jian, Guoqiang Li and Zhiqiang Li    
This paper uses the adaptive dynamic programming (ADP) method to achieve optimal trajectory tracking control for quadrotors. Relying on an established mathematical model of a quadrotor, the approximate optimal trajectory tracking control, which consists ... ver más
Revista: Aerospace

 
Juan Luis Pérez-Ruiz, Yu Tang, Igor Loboda and Luis Angel Miró-Zárate    
In the field of aircraft engine diagnostics, many advanced algorithms have been proposed over the last few years. However, there is still wide room for improvement, especially in the development of more integrated and complete engine health management sy... ver más
Revista: Aerospace

 
Ryota Higashimoto, Soh Yoshida and Mitsuji Muneyasu    
This paper addresses the performance degradation of deep neural networks caused by learning with noisy labels. Recent research on this topic has exploited the memorization effect: networks fit data with clean labels during the early stages of learning an... ver más
Revista: Applied Sciences

 
Woonghee Lee, Mingeon Ju, Yura Sim, Young Kul Jung, Tae Hyung Kim and Younghoon Kim    
Deep learning-based segmentation models have made a profound impact on medical procedures, with U-Net based computed tomography (CT) segmentation models exhibiting remarkable performance. Yet, even with these advances, these models are found to be vulner... ver más
Revista: Applied Sciences

 
Haohao Guo, Tianxiang Xiang, Yancheng Liu, Qiaofen Zhang, Yi Wei and Fengkui Zhang    
This paper proposes a new method for compensating current measurement errors in shipboard permanent magnet propulsion motors. The method utilizes cascade decoupling second-order generalized integrators (SOGIs) and adaptive linear neurons (ADALINEs) as th... ver más