Title :
A Learning Control of Underwater Robotic Vehicles with Thruster Dynamics
Author_Institution :
Department of Mechanical Engineering, Oregon State University, Corvallis, Oregon 97331, USA
Abstract :
Most vehicle control systems based on the simplified vehicle model often result in poor performance because of the nonlinear and time-varying vehicle dynamics as well as thruster dynamics. It is desired to have an advanced control system with capability of learning and adapting to changes in the vehicle dynamics and parameters. This paper describes a learning control system using neural networks for under-water robotic vehicles having a velocity-controlled thruster system. Its effectiveness was investigated by simulation with a single thruster system.
Keywords :
Control system synthesis; Control systems; Neural networks; Nonlinear control systems; Nonlinear dynamical systems; Robot control; Time varying systems; Underwater vehicles; Vehicle dynamics; Velocity control;
Conference_Titel :
American Control Conference, 1993
Print_ISBN :
0-7803-0860-3
