Soft vs. hard bounds in probabilistic robustness analysis

Abstract

The relationship between soft vs. hard bounds and probabilistic vs. worst-case problem formulations for robustness analysis has been a source of some apparent confusion in the control community, and this paper will attempt to clarify some of these issues. Essentially, worst-case analysis involves computing the maximum of a function which measures performance over some set of uncertainty. Probabilistic analysis assumes some distribution on the uncertainty and computes the resulting probability measure on performance. Exact computation in each case is intractable in general, and this paper explores the use of both soft, and hard bounds for computing estimates of performance, including extensive numerical experimentation. We will focus on the simplest possible problem formulations that we believe reveal the difficulties associated with more general robustness analysis.

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