Radially truncated uniform distributions for probabilistic robustness of control systems

B. R. Barmish, Constantino Manuel Lagoa, R. Tempo

Research output: Contribution to journalConference article

29 Citations (Scopus)

Abstract

In this paper, a new approach to probabilistic robustness is developed in the context of unstructured uncertainty. For a control system with a bound on the uncertain quantities of interest, the probabilistic robustness margin Rmax(ε) describes the radius of tolerable uncertainty as a function of the risk level 0≤ε≤1. In addition, associated with the performance risk probability p = ε, the computed radius Rmax(ε) is guaranteed for a large class of radially symmetric nonincreasing density functions. In other words, the results are distribution-free in the sense that the user does not need to have a detailed description of the statistics of the uncertainty other than a radial bound.

Original languageEnglish (US)
Pages (from-to)853-857
Number of pages5
JournalProceedings of the American Control Conference
Volume1
StatePublished - Jan 1 1997
EventProceedings of the 1997 American Control Conference. Part 3 (of 6) - Albuquerque, NM, USA
Duration: Jun 4 1997Jun 6 1997

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Robustness (control systems)
Control systems
Probability density function
Statistics
Uncertainty

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Cite this

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Radially truncated uniform distributions for probabilistic robustness of control systems. / Barmish, B. R.; Lagoa, Constantino Manuel; Tempo, R.

In: Proceedings of the American Control Conference, Vol. 1, 01.01.1997, p. 853-857.

Research output: Contribution to journalConference article

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AU - Lagoa, Constantino Manuel

AU - Tempo, R.

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AB - In this paper, a new approach to probabilistic robustness is developed in the context of unstructured uncertainty. For a control system with a bound on the uncertain quantities of interest, the probabilistic robustness margin Rmax(ε) describes the radius of tolerable uncertainty as a function of the risk level 0≤ε≤1. In addition, associated with the performance risk probability p = ε, the computed radius Rmax(ε) is guaranteed for a large class of radially symmetric nonincreasing density functions. In other words, the results are distribution-free in the sense that the user does not need to have a detailed description of the statistics of the uncertainty other than a radial bound.

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