The design of a navigation guidance and control system for an unmanned surface vehicle for environmental monitoring

Maintaining the ecosystem is one of the main concerns in this modern age. With the fear of ever-increasing global warming, the UK is one of the key players to participate actively in taking measures to slow down at least its phenomenal rate. As an ingredient to this process, the Springer vehicle was designed and developed for environmental monitoring and pollutant tracking. This special issue paper highlighted the Springer hardware and software architecture including various navigational sensors, a speed controller, and an environmental monitoring unit. In addition, details regarding the modelling of the vessel were outlined based mainly on experimental data. The formulation of a fault tolerant multi-sensor data fusion technique was also presented. Moreover, control strategy based on a linear quadratic Gaussian controller was developed and simulated on the Springer model.
Gaussian controller is developed and simulated on the Springer model.

An automatic COLREGs-compliant obstacle avoidance system for an unmanned surface vehicle

Unmanned surface vehicles are becoming increasingly vital tools in a variety of maritime applications. Unfortunately, their usability is severely constrained by the lack of a reliable obstacle detection and avoidance system. In this article, one such experimental platform is proposed, which performs obstacle detection, risk assessment and path planning (avoidance) tasks autonomously in an integrated manner. The detection system is based on a vision-LIDAR (light detection and ranging) system, whereas a heuristic path planner is utilised. A unique property of the path planner is its compliance with the marine collision regulations. It is demonstrated through hardware-in-the-loop simulations that the proposed system can be useful for both uninhabited and manned vessels.

An Autopilot Based on a Local Control Network Design for an Unmanned Surface Vehicle

Over recent years, a number of marine autopilots designed using linear techniques have underperformed owing to their inability to cope with nonlinear vessel dynamics. To this end, a new design framework for the development of nonlinear autopilots is proposed herein. Local control networks (LCNs) can be used in the design of nonlinear control systems. In this paper, a LCN approach is taken in the design of a nonlinear autopilot for controlling the nonlinear yaw dynamics of an unmanned surface vehicle known as Springer. It is considered the approach is the first of its kind to be used in marine control systems design. Simulation results are presented and the performance of the nonlinear autopilot is compared with that of an existing Springer linear quadratic Gaussian (LQG) autopilot using standard system performance criteria. From the results it can be concluded the LCN autopilot out performed that based on LQG techniques in terms of the selected criteria. Also it provided more energy saving control strategies and would thereby increase operational duration times for the vehicle during real-time missions.

Stability Analysis and Implementation of a Decentralized Formation Control Strategy for Unmanned Vehicles

This paper presents a new methodology for solving the multi-vehicle formation control problem. It employs a unique extension-decomposition-aggregation scheme to transform the overall complex formation control problem into a group of subproblems, which work via boundary interactions or disturbances. Thus, it is proved that the overall formation system is exponentially stable in the sense of Lyapunov, if all the individual augmented subsystems (IASs) are stable. Linear matrix inequality-based H8 control methodology is employed to design the decentralized formation controllers to reject the impact of the formation changes being treated as boundary disturbances and guarantee the stability of all the IASs, consequently maintaining the stability of the overall formation system. Simulation studies are performed to verify the stability, performance, and effectiveness of the proposed strategy.

Formation stability analysis of unmanned multi-vehicles under interconnection topologies

In this paper, the overall formation stability of unmanned multi-vehicle is mathematically presented under interconnection topologies. A novel definition of formation error is first given and followed by the proposed formation stability hypothesis. Based on this hypothesis, a unique extension-decomposition-aggregation scheme is then employed to support the stability analysis for the overall multi-vehicle formation under a mesh topology. It is proved that the overall formation control system consisting of N number of nonlinear vehicles is not only asymptotically, but also exponentially stable in the sense of Lyapunov within a neighbourhood of the desired formation. This technique is shown to be applicable for a mesh topology but is equally applicable for other topologies. Simulation study of the formation manoeuvre of multiple Aerosonde UAVs, in 3D-space, is finally carried out verifying the achieved formation stability result.

Co-operative tensegrity-based formation control algorithm for a multi-aircraft system

This paper presents a tensegrity-based co-operative control algorithm for an aircraft formation. The 6 degrees-of-freedom model of the well-known Aerosonde unmanned aerial vehicle (UAV), is integrated with the model of the tensegrity structure and a decentralised control scheme is proposed. The strategy is shown to be scalable for 2n number of UAVs and is able to maintain a firm geometry whilst allowing flexible shape transformations. Simulation results demonstrate the effectiveness and stability of the proposed tensegrity-based formation control algorithm in 3D.

Autonomous COLREGs Compliant Ship Navigation, Using BridgeSimulators and an Unmanned Vessel

This paper presents an approach to COLREGs compliant ship navigation. A system architecture is proposed, which will be implemented and tested on two platforms: networked bridge simulators and at sea trials using an autonomous unmanned surface vessel. Attention is paid to collision avoidance software and its risk mitigation.