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In-Flight Trajectory Planning and Guidance for Autonomous Parafoils
Author(s) -
Branden James Rademacher,
Ping Lu,
Alan Strahan,
Christopher J. Cerimele
Publication year - 2009
Publication title -
journal of guidance control and dynamics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.573
H-Index - 143
eISSN - 1533-3884
pISSN - 0731-5090
DOI - 10.2514/1.44862
Subject(s) - trajectory , control theory (sociology) , proportional navigation , computer science , trajectory optimization , heading (navigation) , range (aeronautics) , aerodynamics , monte carlo method , variable (mathematics) , simulation , optimal control , mathematical optimization , engineering , mathematics , control (management) , aerospace engineering , missile , artificial intelligence , physics , astronomy , mathematical analysis , statistics
This paper presents a framework for onboard trajectory planning and guidance for a large class of autonomously guided parafoils. The problem is for the parafoil to reach a given location at a specified altitude with a specified final heading. Through appropriate change of the independent variable, the trajectory planning problem is converted from a three-dimensional free-final-time problem to a two-dimensional fixed-final-time problem. Using the wellknownDubinspath synthesis andknownparafoil performanceparameters, a concept of altitudemargin is developed as aquantitativemeasure of the availablemaneuvering energy for use in trajectory planning.Ahybrid strategy using two methods to generate kinematically feasible fixed-time trajectories is presented, each targeting a different range of initial values of the altitude margin. The trajectory can be replanned onboard in every guidance cycle, making the guidance effectively closed-loop, or replanned whenever the actual deviation of the actual condition from the reference trajectory exceeds a threshold. The proposed planning and guidance algorithm applies to a large class of parafoil canopies and payloads, which encompasses wide variations in the lift-to-drag ratio, wing loading, and maximum turn rate. The guidance logic has the potential of requiring little or no tuning to accommodate variations in canopy performance. Monte Carlo simulations are conducted to evaluate the effectiveness of the algorithm with dispersions in canopy performance, loading, wind profile errors, navigation uncertainty, using lateral control only, and using both longitudinal and lateral control.

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