Robust Joint State and Parameter Estimation and Controller Integration for Application to a High-Speed Supercavitating Vehicle

Supercavitation is the condition in which a submerged body is enveloped in a gaseous cavitation bubble. The reduced drag within the cavity permits a supercavitating vehicle to travel much faster than a conventional, fully-wetted, submerged vehicle. Although effective in reducing drag, the cavity presents estimation and control challenges due to the time-varying interaction between the vehicle and the wall of the cavity. As a supercavitating vehicle maneuvers through the water, the shape of the cavity as well as the position of the vehicle within the cavity changes. In addition to these challenges common to all supercavitating vehicles, many practical applications may also be limited to low-weight and low-cost inertial measurement units which do not provide full-state feedback.;The objective of the research is to produce a tractable full-envelope controller that enables maneuvering and command tracking for supercavitating vehicles. The developed architecture must yield desired performance in the presence of all nonlinearities and uncertainties in the system and be compatible with low-cost, low-weight sensor suites which lack full state measurement.;The challenges associated with a nonlinear vehicle model, uncertain parameters, evolving cavity, and output feedback are addressed using adaptive control techniques integrated with a joint state and parameter estimator. Specific challenges faced by the joint estimator include parameter estimation during periods of low excitation in the presence of disturbances, as well as parameter estimation with highly correlated regressors. These challenges are discussed and addressed as part of this research.;The research culminates in an integrated robust adaptive controller and joint estimator that provides control, state estimation, and parameter estimation for a supercavitating vehicle. The resulting architecture represents indirect adaptive control of a nonlinear system with output feedback and uncertain parameters. The efficacy of the architecture is verified via a comprehensive large-envelope test-plan.