A New Nonlinear Guidance Logic for Trajectory Tracking

Park, Sanghyuk; Deyst, John; How, Jonathan P.

doi:10.2514/6.2004-4900

Cited by 362 publications

(251 citation statements)

References 4 publications

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“…[5] presented a concept of guidance-based path following using a parameterized geometry of the trajectory to be tracked. [6], [7] presented a nonlinear guidance logic which approximates a proportional-derivative controller of crosstrack error when close to the trajectory to track with an additional element of anticipatory control enabling tight tracking when following curved paths. This guidance logic is similar to proportional navigation (PN) law against a virtual stationary target that moves every time-instant.…”

Section: Introductionmentioning

confidence: 99%

Development and testing of the intercept primitives for planar UAV engagement

Ghosh

Davis

Chung

et al. 2017

2017 International Conference on Unmanned Aircraft Systems (ICUAS)

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Abstract-With the advance in technologies and applications involving unmanned aerial systems cooperation among the autonomous agents within such an unmanned system as well as preparedness for responding to adversarial threat to such a system has become of pivotal importance. A multiphase operational scenario of such cooperative and adversarial engagement, motivated by manned aerial engagement scenarios, is presented in this paper. A Proportional navigation-based integrated guidance methodology is proposed and investigated as a candidate strategy for intercept primitives in such realistic multi-phase UAV engagements. Numerical examples are presented to demonstrate the performance of the proposed guidance strategy for an UAV in such an engagement. Finally, implementation of these guidance laws in a waypoint-based manner, well suited for use in modern-day autopilots of UAVs, is demonstrated in software-in-the-loop simulations, further accelerating future live-fly capabilities for autonomous aerial engagements.

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Section: Introductionmentioning

confidence: 99%

Development and testing of the intercept primitives for planar UAV engagement

Ghosh

Davis

Chung

et al. 2017

2017 International Conference on Unmanned Aircraft Systems (ICUAS)

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“…The Lyapunov method has been used by several authors, in different ways such as for example [15,16,20,22,24,28,33,35,50]. Here we present an original Lyapunov strategy, serving the advantage to be completely smooth, very simple to apply, and with the peculiarity that the circular final manifold is with exactly minimum turning radius.…”

Section: Lyapunov-lasalle-based Stabilizationmentioning

confidence: 99%

Lyapunov and Minimum-Time Path Planning for Drones

et al. 2014

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In this paper, we study the problem of controlling an unmanned aerial vehicle (UAV) to provide a target supervision and/or to provide convoy protection to ground vehicles.We first present a control strategy based upon a Lyapunov-LaSalle stabilization method to provide supervision of a stationary target. The UAV is expected to join a pre-designed admissible circular trajectory around the target which is itself a fixed point in the space.Our strategy is presented for both HALE (High Altitude Long Endurance) and MALE (Medium Altitude Long Endurance) types UAVs. A UAV flying at a constant altitude (HALE type) is modeled as a Dubins vehicle (i.e. a planar vehicle with constrained turning radius and constant forward velocity). For a UAV that might change its altitude (MALE type), we use the general kinematic model of a rigid body evolving in R 3 . Both control strategies presented are smooth and unlike what is usually proposed in the literature these strategies asymptotically track a circular trajectory of exact minimum turning radius.We also present the time-optimal control synthesis for tracking a circle by a Dubins vehicle. This optimal strategy, although much simpler than the point-to-point time-optimal strategy obtained by P. Souères and J.-P. Laumond in the 1990s (see [45]), is very rich.Finally, we propose control strategies to provide supervision of a moving target, that are based upon the previous ones.

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“…An Arduino connected to the trainer port on the remote control enabled a ROS node to command rover's motor speed, motor direction and steering angle. Waypoint following was achieved by implementing the nonlinear guidance control law presented by Park et al [21].…”

Section: F Rover Controlmentioning

confidence: 99%