Complex industrial systems often contain various uncertainties. Hence sophisticated fuzzy
optimization (metaheuristics) techniques have become commonplace; and are currently …

Probabilistic guarantees of safety and performance are important in constrained dynamical
systems with stochastic uncertainty. We consider the stochastic reachability problem, which …

In this work, we address the problem of piecewise affine approximations, that is, to find
piecewise affine functions that well-approximate a given signal. The proposed approach is …

In this article, we consider open-loop solutions to the stochastic optimal control of a linear
dynamical system with an additive non-Gaussian, log-concave disturbance. We propose a …

We propose an affine controller synthesis technique that maximizes the probability of the
state lying in a time-varying collection of safe sets for a Gaussian-perturbed linear time …

We present a data-driven solution to the terminal-hitting stochastic reachability problem for a
Markov control process. We employ a nonparametric representation of the stochastic kernel …

We consider stochastic optimal control of linear dynamical systems with additive non-
Gaussian disturbance. We propose a novel, sampling-free approach, based on Fourier …

While many techniques have been developed for chance constrained stochastic optimal
control with Gaussian disturbance processes, far less is known about computationally …

In this work, we propose a distributionally robust stochastic model predictive control (DR-
SMPC) algorithm to address the problem of multiple two-sided chance constrained discrete …

While many techniques have been developed for chance constrained stochastic optimal
control with Gaussian disturbance processes, far less is known about computationally …