Advertisement

Viability

  • G. Labinaz
  • M. Guay
Part of the Intelligent Systems, Control and Automation: Science and Engineering book series (ISCA, volume 55)

Abstract

Can we stay where we are?

The work presented in this chapter is aimed at providing the computational framework for the fixed point approach given in (Nerode et al., 1995). The approach taken is based on continuous–time viability specifically the work of (Frankowska and Quincampoix, 1991) on the viability kernel of a differential inclusion. The main objective of the work here is to provide a control automaton that can handle sampling explicitly. The governing continuous–time dynamics are represented by a collection of differential inclusions that allows one to capture the effect of dynamic uncertainty in a hybrid system.

Keywords

Sampling Interval Controllability Operator Plant State Independent Case Viability Kernel 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 38.
    H. Frankowska and M. Quincampoix. Viability Kernels of Differential Inclusions with Constraints: Algorithm and Applications. Journal of Mathematical Systems, Estimation, and Control, 1(3):371–388, 1991. MathSciNetGoogle Scholar
  2. 70.
    A. Nerode, J.B. Remmel, and A. Yakhnis. Controllers as Fixed Points of Set-Valued Operators. In Lecture Notes in Computer Science: Hybrid Systems II, volume 999, pages 344–358. Springer-Verlag, New York, 1995. Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  1. 1.Department of Chemical EngineeringQueen’s UniversityKingstonCanada
  2. 2.Department of Chemical EngineeringQueen’s UniversityKingstonCanada

Personalised recommendations