liu.seSearch for publications in DiVA
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Model Predictive Control in Flight Control Design: Stability and Reference Tracking
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
2014 (English)Licentiate thesis, monograph (Other academic)
Abstract [en]

Aircraft are dynamic systems that naturally contain a variety of constraints and nonlinearities such as, e.g., maximum permissible load factor, angle of attack and control surface deflections. Taking these limitations into account in the design of control systems are becoming increasingly important as the performance and complexity of the controlled systems is constantly increasing. It is especially important in the design of control systems for fighter aircraft. These require maximum control performance in order to have the upper hand in a dogfight or when they have to outmaneuver an enemy missile. Therefore pilots often maneuver the aircraft very close to the limit of what it is capable of, and an automatic system (called flight envelope protection system) against violating the restrictions is a necessity.

In other application areas, nonlinear optimal control methods have been successfully used to solve this but in the aeronautical industry, these methods have not yet been established. One of the more popular methods that are well suited to handle constraints is Model Predictive Control (MPC) and it is used extensively in areas such as the process industry and the refinery industry. Model predictive control means in practice that the control system iteratively solves an advanced optimization problem based on a prediction of the aircraft's future movements in order to calculate the optimal control signal. The aircraft's operating limitations will then be constraints in the optimization problem.

In this thesis, we explore model predictive control and derive two fast, low complexity algorithms, one for guaranteed stability and feasibility of nonlinear systems and one for reference tracking for linear systems. In reference tracking model predictive control for linear systems we build on the dual mode formulation of MPC and our goal is to make minimal changes to this framework, in order to develop a reference tracking algorithm with guaranteed stability and low complexity suitable for implementation in real time safety critical systems.

To reduce the computational burden of nonlinear model predictive control several methods to approximate the nonlinear constraints have been proposed in the literature, many working in an ad hoc fashion, resulting in conservatism, or worse, inability to guarantee recursive feasibility. Also several methods work in an iterative manner which can be quit time consuming making them inappropriate for fast real time applications. In this thesis we propose a method to handle the nonlinear constraints, using a set of dynamically generated local inner polytopic approximations. The main benefits of the proposed method is that while computationally cheap it still can guarantee recursive feasibility and convergence.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2014. , 96 p.
Series
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1642
Keyword [en]
Model Predictive Control
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-103742DOI: 10.3384/lic.diva-103742Local ID: LIU-TEK-LIC-2013:76ISBN: 978-91-7519-422-6 (print)OAI: oai:DiVA.org:liu-103742DiVA: diva2:690771
Presentation
2014-02-21, Visionen, Hus B, Campus Valla, Linköpings universitet, Linköping, 10:15 (English)
Opponent
Supervisors
Note

The series name "Linköping studies in science and technology. Licentiate Thesis" is incorrect. The correct series name is "Linköping studies in science and technology. Thesis".

Available from: 2014-01-29 Created: 2014-01-24 Last updated: 2014-01-29Bibliographically approved

Open Access in DiVA

Model Predictive Control in Flight Control Design: Stability and Reference Tracking(1353 kB)5454 downloads
File information
File name FULLTEXT01.pdfFile size 1353 kBChecksum SHA-512
09a495ef31bf553767a1aa58431fd335fa26f985efe2ae4278a4ac72b28b9001d480e4c9de2b3dfd2ab11c21e6cfcbe6c99028c5bbbe31caab807ee2d15eedb7
Type fulltextMimetype application/pdf
omslag(35 kB)21 downloads
File information
File name COVER01.pdfFile size 35 kBChecksum SHA-512
bb5bb01624bfa7a8145f8df18d68019313413f8e766b4359457679da48041cf0062570544ea5dd7f9a555ce646c3903f76b699e16258f30037369b1cd8451bdd
Type coverMimetype application/pdf

Other links

Publisher's full text

Authority records BETA

Simon, Daniel

Search in DiVA

By author/editor
Simon, Daniel
By organisation
Automatic ControlThe Institute of Technology
Control Engineering

Search outside of DiVA

GoogleGoogle Scholar
Total: 5454 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 594 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf