Position, Orientation and Velocity Detection of Unmanned Underwater Vehicles (UUVs) Using an Optical Detector Array.

This paper presents a proof-of-concept optical detector array sensor system to be used in Unmanned Underwater Vehicle (UUV) navigation. The performance of the developed optical detector array was evaluated for its capability to estimate the position, orientation and forward velocity of UUVs with respect to a light source fixed in underwater. The evaluations were conducted through Monte Carlo simulations and empirical tests under a variety of motion configurations. Monte Carlo simulations also evaluated the system total propagated uncertainty (TPU) by taking into account variations in the water column turbidity, temperature and hardware noise that may degrade the system performance. Empirical tests were conducted to estimate UUV position and velocity during its navigation to a light beacon. Monte Carlo simulation and empirical results support the use of the detector array system for optics based position feedback for UUV positioning applications.

Automated estimator parameter selection for an IBM head/disk assembly.

This paper presents the application of a discrete adaptive observer (DAO) to an IBM head/disk assembly system. Because of the difficulties in tuning, a genetic algorithm is implemented off-line to obtain optimal observer parameters for the DAO. Simulations show that the genetic algorithm is successful in choosing appropriate observer gains. Furthermore, as a result of these optimal gains, the observer state and parameter estimates converge accurately and quickly.