Authors: Mae L. Seto
Addresses: Defence R&D Canada, #9 Grove Street, 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 optimisation is achieved through a genetic algorithm (GA) that evaluates solutions based on a full non-linear analysis of the AUV dynamics and control. The AUV dynamics, hydrodynamics, and control have to be well known ahead of time. The agent is implemented on-board the AUV to provide timely re-assignment of the fin control authority (gains), underway, and consequently the mission can continue or a potential vehicle loss 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 optimised gains. The agent|s greatest impact is in the event of a bow fin jam as the remaining three planes cannot depth-keep well without the agent.
Keywords: underactuated AUVs; autonomous underwater vehicles; genetic algorithms; GAs; knowledge-based agents; agent-based systems; fin control authority; fault tolerance; jammed control fins; AUV control; AUV dynamics; hydrodynamics.
International Journal of Intelligent Defence Support Systems, 2011 Vol.4 No.1, pp.3 - 19
Published online: 30 Dec 2010 *Full-text access for editors Access for subscribers Purchase this article Comment on this article