Distributed Flow Estimation for Autonomous Underwater Robots Using POD-based Model Reduction

[+] Author and Article Information
Fengying Dang

Department of Electrical and Computer Engineering, George Mason University, Fairfax, Virginia 22030

Feitian Zhang

Department of Electrical and Computer Engineering, George Mason University, Fairfax, Virginia 22030

1Corresponding author.

ASME doi:10.1115/1.4043118 History: Received May 05, 2018; Revised November 13, 2018


Flow estimation plays an important role in the control and navigation of autonomous underwater robots. This paper presents a novel flow estimation approach that assimilates distributed pressure measurements through coalescing recursive Bayesian estimation and flow model reduction using proper orthogonal decomposition (POD). The proposed flow estimation approach does not rely on any analytical flow model and is thus applicable to many and various complicated flow fields for arbitrarily shaped underwater robots while most of the existing flow estimation methods apply only to those well-structured flow fields with simple robot geometry. This paper also analyzes and discusses the flow estimation design in terms of reduced-order model accuracy, relationship with conventional flow parameters, and distributed senor placement. To demonstrate the effectiveness of the proposed distributed flow estimation approach, two simulation studies, one with a circular-shaped robot and one with a Joukowski-foil-shaped robot, are presented. The application of flow estimation in closed-loop angle-of- attack regulation is also investigated through simulation.

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