Predicting the young’s modulus of defect free radiata pine shooks in finger-jointing using resonance frequency

In this paper, dynamic MOE and static MOE of short-length radiata pine specimens produced for finger jointing were measured using non-destructive technique and correlated to each other. In order to obtain reliable static MOE data, 36 mm thickness shooks as well as the matched samples of reduced thickness (15mm) were tested, and the effect of annual growth rings on dynamic and static MOE is also addressed. Mathematical correlations were fitted between the dynamic MOE for the 36 mm thick shooks and the static MOE of the 15 mm thick samples. The coefficient of determination for dynamic MOE group 4,00-7,99 GPa was the strongest (R2 = 0,82) and the correlation strength was further improved for sorted quarter sawn samples (R2 = 0,92). Finally, the correlation between static modulus of rupture (MOR) and dynamic MOE is discussed

Adaptive neural control of uncertain multi-variable nonlinear systems with saturation and dead-zone

10.1007/978-1-84882-548-2_9Recent Advances in Intelligent Control Systems195-22

Active control of flexible marine risers

10.1016/j.jsv.2008.09.011Journal of Sound and Vibration3204-5758-776JSVI

Top angle control and vibration reduction of flexible marine risers

10.1109/SICE.2008.4654764Proceedings of the SICE Annual Conference794-799PSIA

Dynamic load positioning for subsea installation via adaptive neural control

10.1109/JOE.2010.2041261IEEE Journal of Oceanic Engineering352366-375IJOE

Adaptive control of hydrodynamic loads in splash zone

10.1109/CACSD-CCA-ISIC.2006.4776921Proceedings of the IEEE International Conference on Control Applications1843-184

Control of coupled vessel, crane, cable, and payload dynamics for subsea installation operations

10.1109/TCST.2010.2041931IEEE Transactions on Control Systems Technology191208-220IETT

Robust adaptive neural network control for a class of uncertain MIMO nonlinear systems with input nonlinearities

10.1109/TNN.2010.2042611IEEE Transactions on Neural Networks215796-812ITNN

Load positioning for subsea installation via approximation based adaptive control

10.1109/CCA.2007.4389318Proceedings of the IEEE International Conference on Control Applications723-72