Supercavitation is an attractive option for high-speed motion of underwater vehicles. This is possible due to the massive drop in skin-friction drag when compared to when the vehicle is fully wetted. Computational methods are useful and cost effective alternatives to experimental tests for studying the dynamics of supercavitating vehicles. However, the dynamics of such a vehicle is difficult to model due to the complex nature of the flow physics associated with such a motion. Still, reduced order models have been effectively used to capture the most prominent features associated with the supercavitating vehicle motion. In this dissertation the dynamical systems model consists of a 6 DOF dynamics model along with correlation based models for the cavity and planing. Both fin-supported and planing-supported motion regimes have been considered in studying the open-loop response. The investigation into the open-loop dynamics is devoted mainly to studying the tailslap phenomenon. Controllers have been devised for the nonlinear system using linear optimal control techniques LQR and mu synthesis. Robustness is achieved by including parametric uncertainty in the linear model while using the mu synthesis control technique. Uncertainty is introduced so that the controller effectively deals with the nonlinear system. Receding horizon control is a powerful tool for online controller synthesis for enhanced performance of highly nonlinear systems. A finite receding horizon LQR tracking controller is designed for the supercavitating problem. The forces experienced by the actuator joints are critical from the designer's point of view. These concerns are addressed through a multibody formulation of the vehicle dynamics. The results corroborate a few established properties of the supercavitating motion. Also, a more comprehensive understanding of tailslap and its dependence on various design parameters has been obtained. The control results have given effective inner-loop controllers with satisfactory performance.
展开▼
