Controlled Lagrangian Particle Tracking: Error Growth Under Feedback Control

• Published in: IEEE transactions on control systems technology Vol. 26; no. 3; pp. 874 - 889
• Main Authors: Szwaykowska, Klementyna, Fumin Zhang
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.05.2018; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Autonomous underwater vehicles; Autonomous underwater vehicles (AUVs); Computational modeling; Computer simulation; Control systems; Errors; Feedback control; Gliders; Growth rate; Mathematical model; Model accuracy; model-based control; Navigation; Ocean models; Oceans; Particle tracking; Predictions; Predictive models; stochastic systems; Tracking control; Trajectory; Trajectory measurement; Upper bounds
• ISSN: 1063-6536; 1558-0865
• DOI: 10.1109/TCST.2017.2695161

The method of Lagrangian particle tracking (LPT) is extended to autonomous underwater vehicles (AUVs) that are modeled as controlled particles. Controlled LPT (CLPT) evaluates the performance of ocean models used for the navigation of AUVs by computing the differences between predicted vehicle trajectories and actual vehicle trajectories. Such difference, measured by the controlled Lagrangian prediction error (CLPE), demonstrates growth rate that is influenced by the accuracy of the ocean model and the strength of the feedback control laws used for vehicle navigation. Despite the limited accuracy and resolution of the ocean model, the error growth can be bounded by feedback control when localization service is available, which is a unique property of CLPT. Theoretical relationship among CLPE growth rate, quality of ocean models, and feedback control are established for two control strategies: a transect-following controller and a station-keeping controller that are often used by AUVs. Upper bounds for error growth are derived and verified by both simulation and experimental data collected during the operations of underwater gliders in coastal ocean.