Ship Motion and Air Wake Prediction Using PCA and Fuzzy CMAC

"Maintaining a satisfactory and safe ship operation is very important in Navy operations. An automatic forecast tool that can provide useful information to the ship operator will help to achieve this. The proposed short term forecast tool can learn thenonlinear and time varying relationship between the weather variables such as wind, wave and ship motion. The tool has the necessary learning capability as well as a fast learning speed which is about 10 times faster than conventional neural nets. Henceit is suitable for real-time implementation. The tool can relieve the operator from monitoring the large number of weather variables simultaneously so that he or she can concentrate on making decisions by optimally adjusting the available resources suchas speed and direction of the ship to maintain a satisfactory landing operation. One important advantage of the proposed method is that a custom hardware can be easily designed to implement the forecasting and control tool with reasonably low cost. We willalso use ultrawideband radar to measure wave front parameters such as angle of arrival, range, velocity, and acceleration. The proposed prediction algorithm may be useful for aircraft landing in aircraft carriers. During rough sea conditions, even the bigaircraft carrier may exhibit large motions, which prevent a safe landing. The algorithm will also be useful for container loading. If a forecast tool is available for predicting short-ter