Modeling, Identification, and Control of an Unmanned Surface Vehicle

Abstract

This dissertation addresses the modeling, identification, and control of an automated planing vessel. To provide motion models for trajectory generation and to enable model-based control design for trajectory tracking, several experimentally identified models are compared over a wide range of speed and planing conditions for the Virginia Tech Ribcraft Unmanned Surface Vehicle. The modeling and identification objective is to determine a model which is sufficiently rich to enable effective model-based control design and trajectory optimization, sufficiently simple to allow parameter identification, and sufficiently general to describe a variety of hull forms and actuator configurations. Beginning with a 6 degree of freedom nonlinear dynamic model, several linear steering and speed models are obtained as well as a thruster model.The Ribcraft USV tracks trajectories generated with the selected maneuvering models by using a backstepping trajectory controller. A PD cascade trajectory control law is also developed and the performance of the two controllers is compared using aggressive trajectories. The backstepping control law compares favorably to the PD cascade controller. The backstepping control law is then further modified to account for nonlinear sternward dynamics and for a constant or slowly varying fluid flow. ACKNOWLEDGMENTSThis dissertation is the product of the culmination of years of research and field experimentation that required the collective abilities only found in a group of skilled researchers. There are many people that guided me through the higher level decision-making and advising process as well as the more laborious experimentation and implementation efforts. Without these people I would not have been able to finish a dissertation even approaching this quality.

Adaptive Trajectory Tracking Control for Underactuated Unmanned Surface Vehicle Subject to Unknown Dynamics and Time-Varing Disturbances

“…Based on this, under the premise of input and velocity constraints, dynamic surface control (DSC) technology is used to design a trajectory tracking control strategy for an underactuated ship [15]. For an underactuated USV, the experimental implementation of two trajectory tracking control algorithms: a cascade of proportional-derivative controllers and a nonlinear controller are proposed by Sonnenburg et al through the backstepping control technology [16]. In [17,18], for an underactuated USV, the switching control and modified backstepping methods are used to design the trajectory tracking controller, which can track a straight line track or fixed point.…”

Speed and Heading Control of an Unmanned Surface Vehicle Based on State Error PCH Principle

“…As to the adaptive control, an active mechanism for unmanned vehicles, Klinger et al [3] implemented an adaptive algorithm with the modified backstepping surge controller which has been field tested. Sonnenburg [4] and Sonnenburg and Woolsey [5] direct a speed controller algorithm by backstepping and Lyapunov's direct method, which also has been tested by USV. Dong et al [6] present a state feedback based backstepping control algorithm to address the speed and trajectory tracking problem.…”

Design and validation of an unmanned surface vehicle simulation model

“…Many, if not all, of these models include manoeuvring dynamics only in order to design and test GNC systems [7,8,9,10,11]. By not accounting for the seakeeping dynamics, these models are only applicable to marine craft navigating in calm waters.…”