An increasing variety of sensors are becoming available for use onboard autonomous vehicles. Given these enhanced sensing capabilities, scientific and military personnel are interested in exploiting autonomous vehicles for increasingly complex missions. Most of these missions require the vehicle to function in complex, cluttered environments and react to changing environmental parameters. The present state-of-art vehicles are not maneuverable enough to successfully accomplish most of these tasks. In this research, a nonlinear controller was derived, designed, implemented in simulation and onboard a AUV, and in-water tested in order to enhance vehicle maneuverability. The structure of a controller is hierarchical such that an inner loop non-linear controller (outputs the appropriate thrust values) is the same for all mission scenarios while a library of outer-loop non-linear controllers are available to implement specific maneuvering scenarios. On top of the outer-loop is the mission planner which selects which outer-loop controller will be used. The algorithms are generic and in no way vehicle specific and can therefore be implemented on various AUVs.
Advanced Non-Linear Control Algorithms Applied to Design Highly Maneuverable Autonomous Underwater Vehicles (AUVs)
2007
7 pages
Report
Keine Angabe
Englisch
Electrotechnology , Navigation Systems , Maneuverability , Autonomous navigation , Detectors , Underwater vehicles , Control systems , Clutter , Nonlinear systems , Military personnel , Stability , Algorithms , Computer programs , Symposia , Autonomous vehicles , Nonlinear controllers , Kinematic analysis
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