文献类型： 会议论文

第一作者： Esten Ingar Grotli

作者： Esten Ingar Grotli ¹ ; Joakim Haugen ² ; Tor Arne Johansen ³ ; Lars Imsland ³ ;

作者机构： 1.Department of Mathematics and Cybernetics, SINTEF Digital

2.Department of Fisheries and New Biomarine Industries, SINTEF Ocean

3.Department of Engineering Cybernetics, Norwegian University of Science and Technology

会议名称： American Control Conference

主办单位：

页码： 1515-1522

摘要： In this paper we propose a method for adaptive sampling using Unmanned Aerial Vehicles (UAVs) in oil spill management. The goal is to measure and estimate oil spill concentrations at the sea surface, while at the same time identify the leak rates of sources at known positions. First we construct a cost which approximates the benefit of sampling locations at specific times. This cost is based on measures of observability and of persistency of excitation for the oil spill model. A receding horizon Mixed-Integer Linear Programming (MILP) problem is solved in order to find UAV trajectories which are optimal with respect to the cost. For UAV trajectory tracking we use a Lyapunov based controller. The oil spill concentration measurements taken by the UAVs by following these tracks are used in an adaptive observer, which provides state (concentration) and parameter (leak rate) estimates. Under the assumption that the sampling strategy described above lead to uniform complete observability and persistency of excitation, we prove Uniform Global Asymptotic Stability (UGAS) of the state estimation, parameter identification and UAV trajectory tracking errors. Finally, we provide a simulation of the proposed strategy, and compare it with two other strategies.

分类号： TP273-53