Optimal trim control of a high-speed craft by trim tabs/interceptors Part I: Pitch and surge coupled dynamic modelling using sea trial data

• Published in: Ocean engineering Vol. 130; pp. 300 - 309
• Main Authors: Ertogan, Melek, Wilson, Philip A., Tayyar, Gokhan Tansel, Ertugrul, Seniz
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 15-01-2017
• Subjects: Artificial neural network (ANN); Full-scale experiments; High speed craft dynamics; Linear/nonlinear modelling; System identification (SI); Trim tabs/interceptors; System identification (SI); High speed craft dynamics; Artificial neural network (ANN); Full-scale experiments; Trim tabs/interceptors; Linear/nonlinear modelling
• ISSN: 0029-8018; 1873-5258
• DOI: 10.1016/j.oceaneng.2016.12.007

A pitch and surge coupled dynamic model of a high-speed craft is not available for dynamic trim control applications in the literature. The existing fluid-structure interaction models of a high-speed craft are not adequate for simulations and control applications, since they require a great deal of computation time, for example more than 20–40s depending on a vessel particulars. Hence, in this work, we aimed to obtain a dynamic model of a high-speed craft for surge and pitch motions. Then the obtained model will be utilized to design an automatic controller which adjust the command signal on a high-speed craft to increase fuel efficiency, safety and comfort of passengers in a vessel. The coupled pitch and surge motion of a high-speed craft with trim tabs/interceptors was modelled by using full scale sea trial data. The linear parametric modelling using System Identification (SI) Methods and Artificial Neural Network (ANN) modelling were carried out and the comparisons of both the training and validation results are given. High correlation coefficients and low average values of absolute errors in surge and pitch dynamics were obtained by using ANN Method. The ANN model can be improved for further control designs on a marine vessel's operations.
•Dynamic surge and pitch models were obtained from sea trial data for simulation.•The Neural Network model achieved smaller errors than ARX and Steady-State models.•The ANN model can be used for the simulation and the controller design purposes.•These modelling approach may include other motions such as heave motion.