A covariance-bound procedure yields a high-probability uncertainty set for nonlinear system parameters under unbounded stochastic noise, with convergence guarantees and direct use in probabilistic robust control.
V ershynin, Introduction to the non-asymptotic analysis of random matrices
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Beyond Bounded Noise: Stochastic Set-Membership Estimation for Nonlinear Systems
A covariance-bound procedure yields a high-probability uncertainty set for nonlinear system parameters under unbounded stochastic noise, with convergence guarantees and direct use in probabilistic robust control.