Motion Control of an Autonomous Surface Vessel for Enhanced Situational Awareness

This paper focuses on the critical components of the situational awareness (SA), the controls of position and orientation of an autonomous surface vessel (ASV). Moving of vessel into desired area in particular sea is a challenging but important task for ASVs to achieve high level of autonomy under adverse conditions. With the SA strategy, the approach motion by neural control of an initial stage of an ASV trajectory using neural network predictive controller and the circular motion by control of yaw moment in the final stage of trajectory were proposed. This control system has been demonstrated and evaluated by simulation of maritime maneuvers using software package Simulink. From the simulation results it can be seen that the fast SA of similar ASVs with economy in energy can be asserted during the maritime missions in search-and-rescue operations.

• Igor Astrov
• Mikhail Pikkov
• Rein Paluoja

• Autonomous surface vessels
• neurocontrollers
• situational awareness.

[1] M. R. Endsley, "Toward a theory of situation awareness in dynamic systems,” Human Factors, vol. 37, pp. 32-64, March 1995.
[2] J. Gorman, N. Cooke, and J. Winner, "Measuring team situation awareness in decentralized command and control environments,” Ergonomics, vol. 49, pp. 1312-1325, October 2006.
[3] Interim Brigade Combat Team Newsletter. (Online). Available: http://www.globalsecurity.org/military/library/ report/call/call_01-18_ toc.htm
[4] Unmanned Surface Vehicles. (Online). Available: http://www.gdrs.com/ robotics/programs/program.asp?UniqueID=31
[5] I. Astrov and A. Pedai, "An enhanced situational awareness of a mission for an autonomous underwater vehicle by multirate control,” in Proc. 5th WSEAS International Conf. Dynamical Systems and Control, La Laguna, Tenerife, Canary Islands, Spain, 2009, pp. 33-39.
[6] W. Dong and Y. Guo, "Nonlinear tracking control of underactuated surface vessel,” in Proc. 2005 American Control Conf., Portland, USA, 2005, pp. 4351-4356.
[7] J. M. Maciejowski, Predictive Control with Constraints. London: Prentice Hall, 2002.