EconPapers    
Economics at your fingertips  
 

Minimum Mixed Time–Energy Trajectory Planning of a Nonlinear Vehicle Subject to 2D Disturbances

Ayal Taitler, Ilya Ioslovich (), Erez Karpas () and Per-Olof Gutman ()
Additional contact information
Ayal Taitler: Technion–Institute of Technology
Ilya Ioslovich: Technion–Institute of Technology
Erez Karpas: Technion–Institute of Technology
Per-Olof Gutman: Technion–Institute of Technology

Journal of Optimization Theory and Applications, 2022, vol. 192, issue 2, No 13, 725-757

Abstract: Abstract The problem of a planar vehicle moving on a surface, such as aerial drones or small naval vessels, can be treated as a series of trajectory planning problems between way-points. While nominally the movement between each two fourth-dimensional points (positions and velocities) can be treated as a 1D projection of the movement on the vector connecting the two points, in the presence of arbitrary disturbance the full problem on a plane must be considered. The mixed minimum time–energy optimal solution is now dependent on the value and direction of the disturbance, which naturally affects the structure and completion of the movement task. In this work, we address the minimum time–energy problem of a movement on a 2D plane with quadratic drag, under norm state (velocity) and norm control (acceleration) constraints. The structure and properties of the optimal solution are found and analyzed. The Pontryagin’s maximum principle (PMP) with control and state constraints is utilized. Simulations supporting the results are provided and compared with those of the open-source academic optimal control solver Falcon.m.

Keywords: Optimal control; Variational analysis; Trajectory planning; 49J53; 49K99 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10957-021-01990-0 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:joptap:v:192:y:2022:i:2:d:10.1007_s10957-021-01990-0

Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10957/PS2

DOI: 10.1007/s10957-021-01990-0

Access Statistics for this article

Journal of Optimization Theory and Applications is currently edited by Franco Giannessi and David G. Hull

More articles in Journal of Optimization Theory and Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-20
Handle: RePEc:spr:joptap:v:192:y:2022:i:2:d:10.1007_s10957-021-01990-0