Pradeep Bhatta

Multi-AUV Control and Adaptive Sampling in Monterey Bay

Operations with multiple autonomous underwater vehicles (AUVs) have a variety of underwater applications. For example, a coordinated group of vehicles with environmental sensors can perform adaptive ocean sampling at the appropriate spatial and temporal scales. We describe a methodology for cooperative control of multiple vehicles based on virtual bodies and artificial potentials (VBAP). This methodology allows for adaptable formation control and can be used for missions such as gradient climbing and feature tracking in an uncertain environment. We discuss our implementation on a fleet of autonomous underwater gliders and present results from sea trials in Monterey Bay in August, 2003. These at-sea demonstrations were performed as part of the Autonomous Ocean Sampling Network (AOSN) II project

Multi-AUV control and adaptive sampling in Monterey Bay

Multi-AUV operations have much to offer a variety of underwater applications. With sensors to measure the environment and coordination that is appropriate to critical spatial and temporal scales, the group can perform important tasks such as adaptive ocean sampling. We describe a methodology for cooperative control of multiple vehicles based on virtual bodies and artificial potentials (VBAP). This methodology allows for adaptable formation control and can be used for missions such as gradient climbing and feature tracking in an uncertain environment. We discuss our implementation on a fleet of autonomous underwater gliders and present results from sea trials in Monterey Bay in August 2003. These at-sea demonstrations were performed as part of the Autonomous Ocean Sampling Network (AOSN) II project.

Underwater gliders: recent developments and future applications

Autonomous underwater vehicles, and in particular autonomous underwater gliders, represent a rapidly maturing technology with a large cost-saving potential over current ocean sampling technologies for sustained (month at a time) real-time measurements. We give an overview of the main building blocks of an underwater glider system for propulsion, control, communication and sensing. A typical glider operation, consisting of deployment, planning, monitoring and recovery are described using the 2003 AOSN-II field experiment in Monterey Bay, California. We briefly describe the recent developments at NRC-IOT, in particular, the development of a laboratory-scale glider for dynamics and control research and the concept of a regional ocean observation system using underwater gliders.

Stabilization and coordination of underwater gliders

An underwater glider is a buoyancy-driven, fixed-wing underwater vehicle that redistributes internal mass to control attitude. We examine the dynamics of a glider restricted to the vertical plane and derive a feedback law that stabilizes steady glide paths. The control law is physically motivated and with the appropriate choice of output can be interpreted as providing input-output feedback linearization. With this choice of output, we extend the feedback linearization approach to design control laws to coordinate the gliding motion of multiple underwater gliders.

Nonlinear gliding stability and control for vehicles with hydrodynamic forcing

This paper presents Lyapunov functions for proving the stability of steady gliding motions for vehicles with hydrodynamic or aerodynamic forces and moments. Because of lifting forces and moments, system energy cannot be used as a Lyapunov function candidate. A Lyapunov function is constructed using a conservation law discovered by Lanchester in his classical work on phugoid-mode dynamics of an airplane. The phugoid-mode dynamics, which are cast here as Hamiltonian dynamics, correspond to the slow dynamics in a multi-time-scale model of a hydro/aerodynamically-forced vehicle in the longitudinal plane. Singular perturbation theory is used in the proof of stability of gliding motions. As an intermediate step, the simplifying assumptions of Lanchester are made rigorous. It is further shown how to design stabilizing control laws for gliding motions using the derived function as a control Lyapunov function and how to compute the corresponding regions of attraction.

A Lyapunov function for vehicles with lift and drag: stability of gliding

The energy of a mechanical system naturally provides a Lyapunov function to prove stability of steady motions. This is no longer the case when the system is subject to aerodynamic forces. We derive a Lyapunov function to prove stability of steady, gliding motions for vehicles subject to lift and drag. We make use of a conservation law derived by Lanchester in his original phugoid mode model and in so doing prove conditions under which Lanchesters simplifying assumptions are valid. We apply the results to prove stability and estimate the region of attraction for an underwater glider.

Controlled steady gliding and approximate trajectory tracking for vehicles subject to aerodynamic forcing

In this paper we present a control law that yields exponential stability of steady gliding motions of the conventional take off and landing (CTOL) aircraft model. We interpret the CTOL aircraft model as an interconnected system and prove closed-loop exponential stability by constructing a Lyapunov function. We use the stability of steady gliding motions to propose a methodology for approximately tracking desired trajectories. The stabilization and tracking methods presented here are also applicable to other air and underwater vehicles subject to aerodynamic moments, and lift and drag forces. One of the attractions of tracking based on stable gliding is the very low control effort requirement compared to dynamic inversion based methods. We demonstrate the proposed method with a simulation of the CTOL aircraft model

Cooperative object tracking for many-on-many engagement

This paper presents simulation results of nonlinear filtering algorithms applied to the cooperative object tracking problem. Cooperative tracking refers to observing a object from multiple mobile sensor platforms that communicate with each other, either directly or through a central node. Inter-agent communication also enables cooperative guidance, which can be used to achieve agent formation configurations advantageous to object tracking.

Biological Analogs and Emergent Intelligence for Control of Stratospheric Balloon Constellations

Global Aerospace Corporation is developing a revolutionary concept for a global constellation and network of hundreds of stratospheric superpressure balloons. Global Aerospace Corporation and Princeton University are studying methods of controlling the geometry of these stratospheric balloon constellations using concepts related to and inspiration derived from biological group behavior such as schooling, flocking, and herding. The method of artificial potentials determines control settings for trajectory control systems in the steady flow regions. Weak Stability Boundary theory is used to (a) determine the interfaces between smooth flow and areas where chaotic conditions exist and (b) calculate control settings in regions of chaotic flow.