Robust Optimization is a rapidly developing methodology for handling optimization problems affected by non-stochastic "uncertain-butbounded" data perturbations. In this p...
This paper proposes a quadratic programming (QP) approach to robust model predictive control (MPC) for constrained linear systems having both model uncertainties and bounded distu...
This paper addresses the synthesis approach to output feedback robust model predictive control for systems with polytopic description, bounded state disturbance and measurement no...
BaoCang Ding, YuGeng Xi, Marcin T. Cychowski, Thom...
Probabilistic robustness analysis and synthesis for nonlinear systems with uncertain parameters are presented. Monte Carlo simulation is used to estimate the likelihood of system ...
To solve the cruise two-dimensional revenue management problem and develop such an automated system under uncertain environment, a static model which is a stochastic integer progr...