The discretization of robust quadratic optimal control problems under uncertainty using the finite element method and stochastic collocation leads to large saddle-point systems, which are fully coupled across random realizations. Despite its relevance for numerous engineering problems, solution such systems is notoriusly challenging. In this manuscript, we study efficient preconditioners all-at...

This paper presents a novel approach to the robust solution of optimal impulsive control problems under aleatory and epistemic uncertainty. The uses belief Markov decision processes reformulate problem in terms uncertainty distributions, called beliefs, rather than realizations system states. formulation leads definition where cost function constraints are functions distributions. encompasses o...

The variability of renewable energies and their integration into the grid via power electronics demands design robust control algorithms. This work incorporates two techniques to ensure stability a boost converter through its state equations, implementing inverse optimal gain-scheduling technique for settings. In such way that, under single adjustment, it is capable damping different changes as...

in this paper, we consider a multi-site production planning problem subject to uncertainty in demand and workforce expenses. in our new mathematical model, we presented a production planning system considering failure in rework and breakdown. we also survey human workforce allocation and its expenses which are considered uncertain due to some tradeoff between company’s benefits and workforce :u...