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(2015) Artificial life and computational intelligence, Dordrecht, Springer.
On the estimation of convergence times to invariant sets in convex polytopic uncertain systems
Ryan J. McCloy , José A. De Doná , María M. Seron
pp. 62-75
In this paper, we first provide a mathematical description and proof for the robust stability of systems with convex polytopic uncertainty through the construction of attractive invariant sets. Then, we present the problem of estimating the convergence time to arbitrarily tight over-approximations of an invariant set, from both a known initial condition and for initial conditions belonging to a convex polytopic set. We then propose various analytical and numerical methods for computing the aforementioned convergence time. Finally, a number of numerical examples, including a flexible link robotic manipulator, are given to illustrate the results.
Publication details
DOI: 10.1007/978-3-319-14803-8_5
Full citation:
McCloy, R. J. , De Doná, J. A. , Seron, M. M. (2015)., On the estimation of convergence times to invariant sets in convex polytopic uncertain systems, in M. Randall (ed.), Artificial life and computational intelligence, Dordrecht, Springer, pp. 62-75.
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