Type of Document Dissertation Author Morel, Yannick Author's Email Address ymorel@vt.edu URN etd-04282009-102424 Title Applied Nonlinear Control of Unmanned Vehicles with Uncertain Dynamics Degree PhD Department Mechanical Engineering Advisory Committee
Advisor Name Title Leonessa, Alexander Committee Chair Kurdila, Andrew J. Committee Member Southward, Steve C. Committee Member Stilwell, Daniel J. Committee Member Woolsey, Craig A. Committee Member Keywords
- output feedback
- adaptive control
- nonlinear control
- autonomous vehicles
- collaborative control
- control input saturation
- nonlinear observers
Date of Defense 2009-04-17 Availability unrestricted Abstract The presented research concerns the control of unmanned vehicles. The results introducedin this dissertation provide a solid control framework for a wide class of nonlinear uncertain
systems, with a special emphasis on issues related to implementation, such as control input
amplitude and rate saturation, or partial state measurements availability. More specifically,
an adaptive control framework, allowing to enforce amplitude and rate saturation of the
command, is developed. The motion control component of this framework, which works in
conjunction with a saturation algorithm, is then specialized to different types of vehicles.
Vertical take-off and landing aerial vehicles and a general class of autonomous marine vehicles
are considered. A nonlinear control algorithm addressing the tracking problem for a
class of underactuated, non-minimum phase marine vehicles is then introduced. This motion
controller is extended, using direct and indirect adaptive techniques, to handle parametric
uncertainties in the system model. Numerical simulations are used to illustrate the efficacy
of the algorithms. Next, the output feedback control problem is treated, for a large class of
nonlinear and uncertain systems. The proposed solution relies on a novel nonlinear observer
which uses output measurements and partial knowledge of the system’s dynamics to reconstruct
the entire state for a wide class of nonlinear systems. The observer is then extended
to operate in conjunction with a full state feedback control law and solve both the output
feedback control problem and the state observation problem simultaneously. The resulting
output feedback control algorithm is then adjusted to provide a high level of robustness to
both parametric and structural model uncertainties. Finally, in a natural extension of these
results from motion control of a single system to collaborative control of a group of vehicles,
a cooperative control framework addressing limited communication issues is introduced.
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