Dynamic Positioning System Design for A Marine Vessel with Unknown Dynamics Subject to External Disturbances Including Wave Effect

In this paper, a new control system is proposed for dynamic positioning(DP) of marine vessels with unknown dynamics and subject to external disturbances. The control system is composed of a substructure for wave filtering and state estimation together with a nonlinear PD-type controller. For wave filtering and state estimation, a cascade combination of a modified notch filter and an estimation stage is considered. In estimation stage, a modified extended-state observer(ESO) is proposed to estimate vessel velocities and unknown dynamics. The main advantage of the proposed method is its robustness to model uncertainties and external disturbances and it does not require prior knowledge of vessel model parameters. Besides, the stability of the cascade structure is analyzed and input to state stability(ISS) is guaranteed. Later on, a nonlinear PD-type controller with feedforward of filtered estimated dynamics is utilized. Detailed stability analyses are presented for the closed-loop DP control system and global uniform ultimate boundedness is proved using large scale systems method. Simulations are conducted to evaluate the performance of the proposed method for wave filtering and state estimation and comparisons are made with two conventional methods in terms of estimation accuracy and the presence of uncertainties. Besides, comparisons are made in closed-loop control system to demonstrate the performance of the proposed method compared with conventional methods. The proposed control system results in better performance in the presence of uncertainties,external disturbance and even in transients when the vessel is subjected to sudden changes in environmental disturbances.

Robust Leader-Follower Formation Tracking Control of Multiple Underactuated Surface Vessels

This paper is concerned with the formation control problem of multiple underactuated surface vessels moving in a leader-follower formation. The formation is achieved by the follower to track a virtual target defined relative to the leader. A robust adaptive target tracking law is proposed by using neural network and backstepping techniques. The advantage of the proposed control scheme is that the uncertain nonlinear dynamics caused by Coriolis/centripetal forces, nonlinear damping, unmodeled hydrodynamics and disturbances from the environment can be compensated by on line learning. Based on Lyapunov analysis, the proposed controller guarantees the tracking errors converge to a small neighborhood of the origin. Simulation results demonstrate the effectiveness of the control strategy.

Brief Introduction to a Bionic Lizard Flywheel Planing Craft

Based on the research, simulation and experimental investigation of Basilisk Lizard running on the water surface, and similar experimental investigation of the craft models and practical crafts running on the water surface for about 30 years. The Bionic Lizard Flying Wheel Planing Craft was created and invented. This paper describes the evolution, experimental investigation, test results, design features, advantages, applications, and prospect of the innovation, which denotes the craft with excellent speed performance （high speed, extra STOL （short take-off and landing distance） and VTOL（vertical take-off and landing） characteristics, good transverse and longitudinal stability, super shallow water draft, high propulsion efficiency at high speed without cavitations obstacle, low external field noise, small dimension, simple configuration and structure, good economy, nice transportation efficiency, and possibly is first of these kinds in the HPMV （High Performance Marine Vessels） family around the world.

WARA-PS:a research arena for public safety demonstrations and autonomous collaborative rescue robotics experimentation

A research arena(WARA-PS)for sensing,data fusion,user interaction,planning and control of collaborative autonomous aerial and surface vehicles in public safety applications is presented.The objective is to demonstrate scientific discoveries and to generate new directions for future research on autonomous systems for societal challenges.The enabler is a computational infrastructure with a core system architecture for industrial and academic collaboration.This includes a control and command system together with a framework for planning and executing tasks for unmanned surface vehicles and aerial vehicles.The motivating application for the demonstration is marine search and rescue operations.A state-of-art delegation framework for the mission planning together with three specific applications is also presented.The first one concerns model predictive control for cooperative rendezvous of autonomous unmanned aerial and surface vehicles.The second project is about learning to make safe real-time decisions under uncertainty for autonomous vehicles,and the third one is on robust terrain-aided navigation through sensor fusion and virtual reality tele-operation to support a GPS-free positioning system in marine environments.The research results have been experimentally evaluated and demonstrated to industry and public sector audiences at a marine test facility.It would be most difficult to do experiments on this large scale without the WARA-PS research arena.Furthermore,these demonstrator activities have resulted in effective research dissemination with high public visibility,business impact and new research collaborations between academia and industry.