NDLI: Trajectory generation for a UAV in urban terrain, using nonlinear MPC

Content Provider	IEEE Xplore Digital Library
Author	Singh, L. Fuller, J.
Copyright Year	2001
Description	Author affiliation: United Technol. Res. Center, East Hartford, CT, USA (Singh, L.)
Abstract	This paper describes a receding-horizon optimal control scheme for autonomous trajectory generation and flight control of an unmanned air vehicle in urban terrain. In such environments, the mission objective or terrain may be dynamic, and the vehicle may change dynamics mid-flight due to sensor or actuator failure; thus off-line pre-planned flight trajectories axe limiting and insufficient. This technology is aimed at supporting guidance and control for future missions that will require vehicles with increased autonomy in dangerous situations and with tight maneuvering and operational capability e.g., missions in urban environments. A Model Predictive Control (MPC) scheme is described here that navigates a vehicle with nonlinear dynamics through a vector of known way-points to a goal, and manages constraints. In this MPC-based approach to trajectory planning with constraints, a feedforward nominal trajectory is used to convert the nonconvex, nonlinear optimal control problem into a time-varying linear, convex optimization or quadratic programming problem. The nonconvex, admissible path space is converted to a sequence of overlapping, convex spaces. The feedforward control that produces the nominal trajectory is found from the vehicle's differentially flat outputs. MPC is used to determine the optimal perturbations to the nominal control that will suitably navigate the vehicle through a constrained input/output space while minimizing actuation effort. Simulation results with a non-real-time, online MPC controller for a UAV in a planar urban terrain are included to support the proposed approach.
Sponsorship	American Autom. Control Council
Starting Page	2301
Ending Page	2308
File Size	849529
Page Count	8
File Format	PDF
ISBN	0780364953
ISSN	07431619
DOI	10.1109/ACC.2001.946095
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-06-25
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	American Automatic Control Council(AACC)
Subject Keyword	Unmanned aerial vehicles Optimal control Vehicle dynamics Navigation Trajectory Aerospace control Remotely operated vehicles Actuators Predictive models Predictive control
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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