Identification of Nonlinear Structural Dynamic Systems

Abstract Two methods of system identification of n degrees-of-freedom nonlinear structural dynamic systems are studied and applied to identification of the hydrodynamic coefficient matrices associated with nonlinear drag and linear inertia forces appearing in the equations of motion of offshore structures subjected to wave forces. These two methods, being essentially the methods of state estimation, use nonlinear Kalman filtering algorithms which can be applied to parameter estimation problems by regarding each of the parameters involved in the system as an augmented state variable. One of these methods uses the extended Kalman filter while the other was the iterated linear filter-smoother. Analytical simulation studies are performed for two degrees-of-freedom structural systems on the basis of artificially generated input and output observations under the various output noise conditions. Both methods yield good estimates even under the conditions of fairly large amounts of output noise and are moderately expensive in computer cost.