Optimal Input Design for Parameter Identification of Underwater Vehicles

The accuracy of parameters in a vehicle’s dynamic model strongly affects the dynamic performance of its control system. An optimal input design technique for vehicle parameter estimation is presented in this study. The idea is generated via a dynamic programming method combined with a gradient algorithm for the optimal input synthesis. Also, motion data were analyzed with least squares method so that values of parameters could be estimated. Therefore, the estimated values are compared with arbitrary input signals that are commonly used in parameter identification. This algorithm for selecting optimal inputs is found to be efficient and robust to noises. In summary, this work validated the analysis used to develop the optimal input designs, and demonstrated the feasibility and practical utility of the optimal input design technique by the parameter identification of an underwater glider with fore-and-aft buoyancy engine and an open-framed underwater vehicle.