Title :
Bioinspired Hydrodynamic Force Feedforward for Autonomous Underwater Vehicle Control
Author :
Yiming Xu ; Mohseni, Kamran
Author_Institution :
Dept. of Mech. & Aerosp. Eng., Univ. of Florida, Gainesville, FL, USA
Abstract :
It is believed that the lateral line found in most fish and some other aquatic organisms plays an important role in many behaviors by providing hydrodynamic information about the surrounding fluid. This paper presents a lateral line inspired feedforward control design for the autonomous underwater vehicles. The goal of this paper is to improve maneuvering accuracy for underwater exploration and environmental monitoring. The proposed controller takes pressure measurements at multiple locations over the entire vehicle hull and forms a B-spline surface approximation of the pressure distribution. Hydrodynamic forces acting on the vehicle are then estimated and passed to the controller for the improved trajectory tracking performance. The algorithm is formulated in such a way that the force estimation is a linear, fixed weight combination of the pressure signals, which enables rapid online computation. The performance of the feedforward controller is simulated in conjunction with the “robust integral of the sign of the error” control design. Trajectory tracking is investigated for control accuracy in the presence of localization errors. Reduced tracking errors are observed with the feedforward design. Experimental tests with pressure sensors on a moving cylinder further vindicate the force estimation algorithm.
Keywords :
approximation theory; autonomous underwater vehicles; control system synthesis; feedforward; hydrodynamics; pressure measurement; pressure sensors; robust control; splines (mathematics); B-spline surface approximation; autonomous underwater vehicle control; bioinspired hydrodynamic force feedforward controller; environmental monitoring; error sign robust integral control design; hydrodynamic force estimation; hydrodynamic information; improved trajectory tracking performance; lateral line inspired feedforward control design; pressure distribution; pressure measurements; pressure sensors; pressure signals; underwater exploration; vehicle hull; Estimation; Feedforward neural networks; Force; Hydrodynamics; Sensors; Vectors; Vehicles; Feedforward systems; least squares methods; marine vehicles; surface fitting;
Journal_Title :
Mechatronics, IEEE/ASME Transactions on
DOI :
10.1109/TMECH.2013.2271037