<abstract xml:lang="en" xmlns="http://www.w3.org/1999/xhtml"><p>Our aim is to adapt Fletcher's filter approach to solve optimal control problems for systems described by nonlinear Partial Differential Equations (PDEs) with state constraints. To this end, we propose a number of modifications of the filter approach, which are well suited for our purposes. Then, we discuss possible ways of cooperation between the filter method and a PDE solver, and one of them is selected and tested.</p></abstract>

Our aim is to adapt Fletcher's filter approach to solve optimal control problems for systems described by nonlinear Partial Differential Equations (PDEs) with state constraints. To this end, we propose a number of modifications of the filter approach, which are well suited for our purposes. Then, we discuss possible ways of cooperation between the filter method and a PDE solver, and one of them is selected and tested.

A modified filter SQP method as a tool for optimal control of nonlinear systems with spatio-temporal dynamics

Institute of Computer Engineering, Control and Robotics, Wrocław University of Technology, Wybrzeże Wyspiańskiego 27, 50-370 Wrocław, Poland

International Journal of Applied Mathematics and Computer Science

Our aim is to adapt Fletcher's filter approach to solve optimal control problems for systems described by nonlinear Partial Differential Equations (PDEs) with...

A modified filter SQP method as a tool for optimal control of nonlinear systems with spatio-temporal dynamics

Published Online: Jun 28, 2012

Page range: 313 - 326

DOI: https://doi.org/10.2478/v10006-012-0023-8

Keywords
filter approach, nonlinear programming, optimal control, partial differential equations

This content is open access.

A modified filter SQP method as a tool for optimal control of nonlinear systems with spatio-temporal dynamics

Published Online: Jun 28, 2012

Page range: 313 - 326

DOI: https://doi.org/10.2478/v10006-012-0023-8

Keywordsfilter approach, nonlinear programming, optimal control, partial differential equations

This content is open access.

Keywords
filter approach, nonlinear programming, optimal control, partial differential equations