LPV Control Design for Autonomous Underwater Vehicles Using Robustness Analysis Tools

Abstract This paper deals with the design and analysis of a linear parameter-varying (LPV) path-following controller for an autonomous underwater vehicle (AUV). The LPV controller is designed to provide guaranteed performance for any planar path whose inverse radius of curvature is bounded. Such a flexibility provided by the LPV controller offers significant advantages in AUV missions such as seabed mapping and mine countermeasures. The control design approach uses a lumped system model that is based on a virtual vehicle formulation and combines the six degrees-of-freedom AUV dynamics with the path-following dynamics. An LPV path-following controller is designed using the l2-induced norm as the performance measure and the inverse radius of curvature of the path as the scheduling parameter. The penalty weights of the controller are tuned using a tool that utilizes integral quadratic constraint (IQC) theory to perform robustness analysis. The robustness and performance of the LPV controller are studied using IQC analysis and non-deterministic MATLAB simulations where hydrodynamic model uncertainties, unmodeled servo dynamics, AUV nonlinear dynamics, and sensor noise are considered.