203
Views
0
CrossRef citations to date
0
Altmetric
Research Articles

A novel unified framework for solving reachability and invariance problems

, , &
Pages 1436-1447 | Received 12 May 2021, Accepted 01 Mar 2022, Published online: 23 Mar 2022
 

Abstract

The level set method is a widely used tool for solving reachability and invariance problems. However, some shortcomings, such as large amount of storage space consumption and the difficulty of constructing terminal conditions for solving the Hamilton–Jacobi partial differential equation, limit the application of the level set method in some problems, especially those with irregular target sets. This paper proposes a method that can effectively avoid the above tricky issues and thus has better generality. In the proposed method, the reachable or invariant sets with different time horizons are characterised by some non-zero sublevel sets of a value function. This value function is not obtained by solving a viscosity solution of the partial differential equation but by recursion and interpolation approximation. At the end of this paper, some examples are taken to illustrate the accuracy and generality of the proposed method.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by National Defense Outstanding Youth Science Foundation [2018-JCJQ-ZQ-053] and Central University Basic Scientific Research Operating Expenses Special Fund Project Support [NF2018001].

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 1,709.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.