Virginia Center for Autonomous Systems
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The Virginia Center for Autonomous Systems (VaCAS) is an ICTAS/College of Engineering research center which facilitates interdisciplinary research in autonomous systems technology. VaCAS hosts research activities spanning every application domain: water, land, air, and space. VaCAS member research activities range from fundamental control theory to vehicle development to applications for science, security, and commerce.
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Browsing Virginia Center for Autonomous Systems by Content Type "Technical report"
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- Control-Oriented Planar Motion Modeling of Unmanned Surface VehiclesSonnenburg, C.; Gadre, Aditya; Horner, D.; Krageland, S.; Marcus, A.; Stilwell, Daniel J.; Woolsey, Craig A. (Virginia Center for Autonomous Systems, 2010)This technical report describes a comparison of experimentally identified dynamic models for the planar motion of an unmanned surface vehicle (USV). The objective is to determine a model which is (1) sufficiently rich to enable effective model-based control design, (2) sufficiently simple to allow straight forward parameter identification, and (3) sufficiently general to apply to a variety of hullforms and actuator configurations. Starting from a three degree-of-freedom nonlinear model obtained from physical principles, we consider five simplified variants that include four linear models and two nonlinear models for low speed operation. The first linear model comes from linearizing the full planar boat dynamics about a straight constant speed. A first order steering model relates steering angle to turn rate. A second order steering model relates steering angle to turn rate and sideslip angle. A first order speed model relates throttle setting to forward speed. The two nonlinear models are derived from potential flow around a simple shape. Linear damping and quadratic damping are included in each nonlinear model respectively. To identify parameters for these models, data must be collected that show the dynamic and steady-state relationships between inputs and outputs. Using these data sets, simple models that satisfy the three given criteria are identified for three types of unmanned surface vehicle: a rigid hull inflatable boat with an outboard engine, a rigid hull inflatable boat with a waterjet propulsion system, and a small pontoon boat with two electric thrusters.
- Dynamics & Control of Underwater Gliders II: Motion Planning and ControlMahmoudian, N.; Woolsey, Craig A. (Virginia Center for Autonomous Systems, 2010)This paper describes an underwater glider motion control system intended to enhance locomotive efficiency by reducing the energy expended by vehicle guidance and control. In previous work, the authors derived an approximate analytical expression for steady turning motion by applying regular perturbation theory to a sophisticated vehicle dynamic model. Using these steady turn solutions, including the special case of wings level glides, one may construct feasible paths for the gliders to follow. Because the turning motion results are only approximate, however, and to compensate for model and environmental uncertainty, one must incorporate feedback to ensure precise path following. This report describes the development and numerical implementation of a feedforward/feedback motion control system for a multi-body underwater glider model. Since the motion control system relies largely on steady motions, it is intrinsically efficient. Moreover, the nature of the steady turn approximations suggests a method for nearly energy-optimal path planning.
- Dynamics and Control of Underwater Gliders I: Steady MotionsMahmoudian, N.; Geisbert, J.; Woolsey, Craig A. (Virginia Center for Autonomous Systems, 2007)This paper describes analysis of steady motions for underwater gliders, a type of highly efficient underwater vehicle which uses gravity for propulsion. Underwater gliders are winged underwater vehicles which locomote by modulating their buoyancy and their attitude. Several such vehicles have been developed and have proven their worth as efficient long-distance, long-duration ocean sampling platforms. To date, the primary emphasis in underwater glider development has been on locomotive efficiency; maneuverability has been a secondary concern. The ultimate aim of our research is to develop optimal motion control strategies which enhance the natural locomotive efficiency of underwater gliders by minimizing the energy expended by the control system. Ambitious applications such as persistent undersea surveillance require not only efficient vehicles, but efficient guidance and control schemes. This technical report aims to develop a better understanding of glider maneuverability, particularly with regard to turning motions. As a preliminary step, we develop an approximate analytical expression for steady turning motion for a realistic glider model. The problem is formulated in terms of regular perturbation theory, with the vehicle turn rate as the perturbation parameter. The resulting solution exhibits a special structure that allows one to apply existing optimal path planning results for planar mobile robots. The ultimate result is a simple, energy-efficient motion control method for underwater gliders.
- Nonlinear Estimation with State-Dependent Gaussian Observation NoiseSpinello, D.; Stilwell, Daniel J. (Virginia Center for Autonomous Systems, 2008)We consider the problem of estimating the state of a system when measurement noise is a function of the system's state. We propose generalizations of the iterated extended Kalman filter and of the extended Kalman filter that can be utilized when the state estimate distribution is approximately Gaussian. The state estimate is computed by an iterative root-searching method that maximize a maximum likelihood function. For sensor network applications, we also address distributed implementations involving multiple sensors.
- Optimal Control of an Undersea Glider in a Symmetric Pull-upKraus, R.; Cliff, Eugene M.; Woolsey, Craig A.; Luby, J. (Virginia Center for Autonomous Systems, 2008)An undersea glider is a winged autonomous undersea vehicle which modulates its buoyancy to rise or sink and moves its center of mass to control pitch and roll attitude. By properly phasing buoyancy and pitch control, an undersea glider rectifies the vertical motion caused by changes in buoyancy into forward motion caused by the lift force on the fixed wing. The characteristic "porpoising" motion is useful in oceanographic surveys and the propulsion method is extremely efficient - undersea gliders routinely operate for months without human intervention. Glider efficiency could be improved even further by addressing the phenomenon of "stall" (loss of lift) when a glider transitions from downward to upward flight. Because the stall phenomenon occurs asymmetrically over the vehicle's wing, it can cause directional errors which must be corrected at a corresponding energetic cost. This paper describes the formulation of a point mass model and its dynamic equations of motion. An optimal control formulation was designed using angle of attack and buoyancy as controls to investigate control scheduling methods for avoiding stall in a symmetric pull-up. The calculations were repeated using three different numerical solution techniques for comparison of the methodologies and results. The model was updated to include longitudinal rigid body dynamics and changed the control to the rate of change of the longitudinal center of gravity location. This model allowed for the inclusion of added mass effects due to fluid displacement.
- Sensor Error Model for a Uniform Linear ArrayGadre, Aditya; Roan, Michael J.; Stilwell, Daniel J. (Virginia Center for Autonomous Systems, 2008)We derive a measurement error model for a uniform linear array whose output is the bearing to a single narrowband acoustic source. The measurement error depends on various array as well as environmental parameters, which include the number of hydrophones in the array, spacing between adjacent hydrophones, frequency of the acoustic signal, speed of sound and signal-to-noise ratio. Most importantly, we show that the measurement error is a function of the true bearing from the array to the acoustic source.
- Under-actuated Controllability for Spacecraft RendezvousRogers, Andrew; Woolsey, Craig A.; McGwier, Robert W. (Virginia Tech, 2014-06-27)In this report, we examine the controllability of a particular form of the equations of motion for spacecraft formation flying. These equations, the Tschauner-Hempel equations, rescale the formation flying equations to a domain in which the true anomaly is the independent variable. Using this form, we are able to compute an explicit, closed-form Gramian matrix for the period of one full orbit at arbitrary eccentricity. We do this for two cases: 1) the case in which there are three inputs to the system as well as 2) the restricted case where authority only exists in the in-track and cross-track directions. This Gramian is invertible and as a result the system is controllable for both cases. Since the transformation between the time-domain, linear equations of motion and the Tschauner-Hempel equations is bijective, we conclude that the linear equations of motion are also controllable.
- Vehicle Dynamics in CurrentsWoolsey, Craig A. (Virginia Center for Autonomous Systems, 2011)Vehicles operating in non-uniform flow fields are subject to forces and moments that are not captured by kinematic motion models. These effects are even greater when the mass of the displaced fluid is commensurate with the mass of the vehicle, as is the case for maritime vehicles and airships. Following along the lines of a recent paper by Thomasson, this report presents a dynamic model for the motion of a rigid vehicle in a non-uniform flow. The flow field is assumed to be irrotational, comprising a steady, non-uniform component and an unsteady, uniform component. As Thomasson suggests, rotational flow effects can be incorporated by modifying the vehicle's angular rate when computing viscous forces and moments. These equations have a variety of applications for modeling, simulation, and design, a few of which are listed at the end of the report.