A Time-Varying Lookahead Distance of ILOS Path Following for Unmanned Surface Vehicle

This paper investigates the path following control problem for an underactuated unmanned surface vehicle (USV) in the presence of dynamical uncertainties and time-varying external disturbances. Based on fuzzy optimization algorithm, an improved adaptive line-of-sight (ALOS) guidance law is proposed, which is suitable for straight-line and curve paths. On the basis of guidance information provided by LOS, a three-degree-of-freedom (DOF) dynamic model of an underactuated USV has been used to design a practical path following controller. The controller is designed by combining backstepping method, neural shunting model, neural network minimum parameter learning method, and Nussbaum function. Neural shunting model is used to solve the problem of “explosion of complexity,” which is an inherent illness of backstepping algorithm. Meanwhile, a simpler neural network minimum parameter learning method than multilayer neural network is employed to identify the uncertainties and time-varying external disturbances. In particular, Nussbaum function is introduced into the controller design to solve the problem of unknown control gain coefficient. And much effort is made to obtain the stability for the closed-loop control system, using the Lyapunov stability theory. Simulation experiments demonstrate the effectiveness and reliability of the improved LOS guidance algorithm and the path following controller.

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Robust steering assistance control for tracking large-curvature path considering uncertainties of driver’s steering behavior

Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering ◽

10.1177/0954407020976827 ◽

2021 ◽

pp. 095440702097682

Author(s):

Jinxiang Wang ◽

Zhenwu Fang ◽

Mengmeng Dai ◽

Guodong Yin ◽

Jingjing Xia ◽

...

Keyword(s):

Path Following ◽

Vehicle Speed ◽

Time Varying ◽

Steering Control ◽

Characteristic Parameters ◽

Parameter Uncertainties ◽

Large Curvature ◽

Steering Characteristics ◽

Dynamic Compensator ◽

Takagi Sugeno

A human-machine shared steering control is presented in this paper for tracking large-curvature path, considering uncertainties of driver’s steering characteristics. A driver-vehicle-road (DVR) model is proposed in which uncertain characteristic parameters are defined to describe the human driver’s steering behaviors in tracking large-curvature path. Then the radial basis function neural network (RBF) is used to estimate parameters of different drivers’ characteristics and to obtain the boundaries of these parameters. Parameter uncertainties of the driver’s steering characteristics and time-varying vehicle speed of the DVR model are handled with the Takagi-Sugeno (T-S) fuzzy logic. And these parameter uncertainties are considered in the design of the shared steering controller. Then based on the DVR model, a T-S fuzzy full-order dynamic compensator with D-pole assignment is designed to assist driver’s steering for tracking path with large curvature. Simulation results show that the proposed controller can provide individual levels of steering assistance in path following according to driver’s proficiency, and can improve driving comfort significantly.

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Line-of-sight guidance law for path following of amphibious hovercrafts with big and time-varying sideslip compensation

Ocean Engineering ◽

10.1016/j.oceaneng.2018.12.036 ◽

2019 ◽

Vol 172 ◽

pp. 531-540 ◽

Cited By ~ 8

Author(s):

Yuanhui Wang ◽

Haiyan Tong ◽

Mingyu Fu

Keyword(s):

Path Following ◽

Line Of Sight ◽

Time Varying ◽

Guidance Law

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Adaptive Fast Non-Singular Terminal Sliding Mode Path Following Control for an Underactuated Unmanned Surface Vehicle with Uncertainties and Unknown Disturbances

Sensors ◽

10.3390/s21227454 ◽

2021 ◽

Vol 21 (22) ◽

pp. 7454

Author(s):

Yunsheng Fan ◽

Bowen Liu ◽

Guofeng Wang ◽

Dongdong Mu

Keyword(s):

Actuator Saturation ◽

Sliding Mode ◽

Path Following ◽

Design Parameters ◽

Real Time Control ◽

Sideslip Angle ◽

Terminal Sliding Mode ◽

Unmanned Surface Vehicle ◽

Control Approach ◽

Unknown Disturbances

This paper focuses on an issue involving robust adaptive path following for the uncertain underactuated unmanned surface vehicle with time-varying large sideslips angle and actuator saturation. An improved line-of-sight guidance law based on a reduced-order extended state observer is proposed to address the large sideslip angle that occurs in practical navigation. Next, the finite-time disturbances observer is designed by considering the perturbations parameter of the model and the unknown disturbances of the external environment as the lumped disturbances. Then, an adaptive term is introduced into Fast Non-singular Terminal Sliding Mode Control to design the path following controllers. Finally, considering the saturation of actuator, an auxiliary dynamic system is introduced. By selecting the appropriate design parameters, all the signals of the whole path following a closed-loop system can be ultimately bounded. Real-time control of path following can be achieved by transferring data from shipborne sensors such as GPS, combined inertial guidance and anemoclinograph to the Fast Non-singular Terminal Sliding Mode controller. Two examples as comparisons were carried out to demonstrate the validity of the proposed control approach.

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