Adaptive control of hydrodynamic loads in splash zone

In this paper, adaptive control for hydrodynamic forces acting on payloads going through the splash zone are investigated using model-based and non-model-based (neural network) parameterization techniques. After the presentation of a detailed mathematical model for hydrodynamic loads during water entry, model-based and non-model-based robust adaptive controllers are developed with closed-loop stability. Intensive computer simulations are carried out to show the effectiveness of the proposed control techniques. It is observed that as the parameterization techniques can capture the dominant dynamic behaviors, higher feedback gains for model-based control can be used and the speed of adaptation can also be increased for better control performance. It is also found that neural networks are suitable candidates for the modeling and adaptive controller design of hydrodynamic loads