### 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 R_{max}(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 R_{max}(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 language | English (US) |
---|---|

Pages (from-to) | 853-857 |

Number of pages | 5 |

Journal | Proceedings of the American Control Conference |

Volume | 1 |

State | Published - Jan 1 1997 |

Event | Proceedings of the 1997 American Control Conference. Part 3 (of 6) - Albuquerque, NM, USA Duration: Jun 4 1997 → Jun 6 1997 |

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### All Science Journal Classification (ASJC) codes

- Electrical and Electronic Engineering

### Cite this

*Proceedings of the American Control Conference*,

*1*, 853-857.

}

*Proceedings of the American Control Conference*, vol. 1, pp. 853-857.

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

Research output: Contribution to journal › Conference article

TY - JOUR

T1 - Radially truncated uniform distributions for probabilistic robustness of control systems

AU - Barmish, B. R.

AU - Lagoa, Constantino Manuel

AU - Tempo, R.

PY - 1997/1/1

Y1 - 1997/1/1

N2 - 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.

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.

UR - http://www.scopus.com/inward/record.url?scp=0030652801&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0030652801&partnerID=8YFLogxK

M3 - Conference article

VL - 1

SP - 853

EP - 857

JO - Proceedings of the American Control Conference

JF - Proceedings of the American Control Conference

SN - 0743-1619

ER -