Accurate ship motion prediction is crucial for safe and efficient operations at sea. Previously studied Single Input Single Output (SISO) system-based method often falls short in providing robust and precise predictions. This thesis explores the potential of using a Multiple Inputs Multiple Outputs (MIMO) system identification approach to provide more accurate and ro- bust ship motion prediction in offshore operations.
We investigate two MIMO systems, the force-to-motion system and wave-to-motion system, employing Spectral Analysis method and Subspace method, respectively. Both synthetic and real-field data are utilized to study the methods. While Spectral Analysis method demon- strates better accuracy, it relies on the assumption of perfect accuracy of the pre-computed force Response Amplitude Operators (RAOs), which is a limitation of this approach. Sub- space method is less precise, it also requires real-time re-evaluation of the system order due to its sensitivity to wave conditions, making this method less versatile.
Comparing these methods with SISO system method and conventional RAO-based method, Spectral Analysis method emerges as the most accurate, followed by Subspace method. These findings strongly support the potential of MIMO system identification to significantly improve ship motion prediction accuracy.