Identification of slow drift motions of a truss spar platform using parametric Volterra model

dentification of the first and second-order surge motion transfer functions of a truss spar platform from model test data is presented in this paper. The identification is carried out by estimating the time-varying kernels coefficients of a second-order Volterra model. The coefficients are estimated using proposed method, named particle swarm optimization based Kalman smoother (PSO-KS). System input–output data for identification process are wave height and surge motion from a scaled 1:100 model of a prototype truss spar. The applicability of proposed method is assessed numerically and experimentally under unidirectional long-crested random waves. The results show that the linear and quadratic frequency response functions (LFRF and QFRF) as well as the wave and low frequency responses of a truss spar platform can be well identified either in time or frequency domains. The LFRF and QFRF have high resolution so that evolution of the nonlinear wave interactions can be revealed.