Design of reduced complexity controllers for linear systems under constraints using data cluster analysis-Reference-Cited by-同舟云学术

Design of reduced complexity controllers for linear systems under constraints using data cluster analysis

Published:2020-09-22 Issue:14 Volume:51 Page:2533-2548
ISSN:0020-7721
Container-title:International Journal of Systems Science
language:en
Short-container-title:International Journal of Systems Science

Author:

Dantas Amanda D. O. S.¹^ORCID,Dantas André F. O. A.¹²^ORCID,Almeida Túlio F. D.²^ORCID,Dórea Carlos E. T.³^ORCID

Affiliation:

1. Potiguar University, School of Exact and Technological Sciences, Natal, Brazil

2. Graduate Program in Neuroengineering – Edmond and Lily Safra International Institute of Neurosciences (IIN-ELS), Santos Dumont Institute (ISD), Macaíba, Brazil

3. Computer and Automation Engineering Department (DCA), Federal University of Rio Grande do Norte, Natal, Brazil

Publisher

Informa UK Limited

Subject

Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/00207721.2020.1795948

Reference41 articles.

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3. Athanasopoulos, N. & Bitsoris, G. (2009). A novel approach to the computation of the maximal controlled invariant set for constrained linear systems. In2009 European control conference (ECC)(pp. 3124–3129). IEEE.

4. Athanasopoulos, N. & Bitsoris, G. (2010). Invariant set computation for constrained uncertain discrete-time linear systems. In49th IEEE conference on decision and control (CDC)(pp. 5227–5232). IEEE.

5. Model predictive control based on linear programming - the explicit solution

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