Robust global uniform asymptotic stabilization of underactuated surface vessels with unknown model parameters

2013 ◽  
Vol 25 (7) ◽  
pp. 1037-1050 ◽  
Author(s):  
Wenjing Xie ◽  
Baoli Ma
Keyword(s):  
Model Parameters ◽  
Asymptotic Stabilization ◽  
Surface Vessels ◽  
Underactuated Surface Vessels

scholarly journals Neural Network-Based Fault-Tolerant Control of Underactuated Surface Vessels

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Bong Seok Park
Keyword(s):  
Degrees Of Freedom ◽  
Fault Tolerant ◽  
Model Parameters ◽  
External Disturbances ◽  
Detection Scheme ◽  
Surface Vessels ◽  
Additional Control ◽  
Underactuated Surface Vessels ◽  
Path Stability ◽  
Multilayer Neural Networks

This paper addresses the problem of trajectory tracking of underactuated surface vessels (USVs) in the presence of thruster failure. Multilayer neural networks (MNNs) are employed to estimate the unknown model parameters and external disturbances. To design a fault-tolerant controller without a fault detection scheme, we use the Nussbaum gain technique. We introduce an additional control to resolve the difficulty arising from having fewer inputs than degrees-of-freedom. Further, an approach angle is proposed to track both a straight and curved path. Stability analysis and simulations are performed to demonstrate the effectiveness of the proposed scheme.

scholarly journals Asymptotic stabilization of underactuated surface vehicles with actuator saturation

2021 ◽  
Vol 7 ◽  
pp. e793
Author(s):  
Pengfei Zhang ◽  
Tingting Yang
Keyword(s):  
Convergence Rates ◽  
Actuator Saturation ◽  
Input Saturation ◽  
Fractional Power ◽  
Control Laws ◽  
Asymptotic Stabilization ◽  
Global Asymptotic Stabilization ◽  
Surface Vessels ◽  
Underactuated Surface Vessels ◽  
Cascade Structure

This paper investigates the problem of global asymptotic stabilization of underactuated surface vessels (USVs) with input saturation. A novel input transformation is presented, so that the USV system can be transformed to a cascade structure. For the obtained system, the improved fractional power control laws are proposed to ensure input signals do not exceed actuator constraints and enhance convergence rates. Finally, stabilization and parameter optimization algorithm of USVs are proposed. Simulations are given to demonstrate the effectiveness of the presented method.

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