Title :
On-board AUV autonomy through adaptive fins control
Author :
Seto, Mae L. ; Li, Howard
Author_Institution :
Mine & Harbour Defence Group at Defence R&D Canada, Dartmouth, NS, Canada
Abstract :
A knowledge-based agent was designed and validated to optimally re-distribute control authority in a torpedo-shaped autonomous underwater vehicle (AUV). The objective is greater fault tolerance in AUVs on long deployments when an AUV is unexpectedly underactuated from a jammed control fin. The optimization is achieved through a genetic algorithm that evaluates solutions based on a full non-linear analysis of the AUV dynamics and control. The agent is implemented on-board the AUV to provide timely reassignment of the fin control authority (gains) while underway so that the mission can continue or a potential vehicle loss be averted. The effectiveness of the agent is assessed through a parametric analysis that compares the response of the unexpectedly underactuated AUV with its initial gains against the optimized gains. The agent´s greatest impact is in the event of a bow fin jam as the remaining functional planes maintain depth better with the agent´s help. The ability to provide a timely and on-board optimal solution that adapts to a fin jam is a higher level of autonomy than has been previously reported.
Keywords :
adaptive control; fault tolerance; genetic algorithms; knowledge based systems; mobile robots; nonlinear control systems; optimal control; remotely operated vehicles; underwater vehicles; AUV control; adaptive fins control; fault tolerance; genetic algorithm; jammed control fin; knowledge-based agent; nonlinear analysis; on-board AUV autonomy; optimally re-distribute control authority; torpedo-shaped autonomous underwater vehicle; Attitude control; Hydrodynamics; Jamming; Space vehicles; Trajectory; Vehicle dynamics;
Conference_Titel :
Automation Science and Engineering (CASE), 2010 IEEE Conference on
Conference_Location :
Toronto, ON
Print_ISBN :
978-1-4244-5447-1
DOI :
10.1109/COASE.2010.5584067