The aim of the paper is to provide a linearization approach to the $\mathrm{See\; PDF}$-control problems. We begin by proving a semigroup-type behaviour of the set of constraints appearing in the linearized formulation of (standard) control problems. As a byproduct we obtain a linear formulation of the dynamic programming principle. Then, we use the $\mathrm{See\; PDF}$ approach and the associated linear formulations. This seems to be the most appropriate tool for treating $\mathrm{See\; PDF}$ problems in continuous and lower semicontinuous setting.

The aim of the paper is to provide a linearization approach to the ${𝕃}^{\infty }$See PDF-control problems. We begin by proving a semigroup-type behaviour of the set of constraints appearing in the linearized formulation of (standard) control problems. As a byproduct we obtain a linear formulation of the dynamic programming principle. Then, we use the ${𝕃}^p$See PDF approach and the associated linear formulations. This seems to be the most appropriate tool for treating ${𝕃}^{\infty }$See PDF problems in continuous and lower semicontinuous...

On a closed convex set $Z$ in ${ℝ}^N$ with sufficiently smooth (${𝒲}^{2,\infty }$) boundary, the stop operator is locally Lipschitz continuous from ${𝐖}^{1,1}([0,T],{ℝ}^N)\times Z$ into ${𝐖}^{1,1}([0,T],{ℝ}^N)$. The smoothness of the boundary is essential: A counterexample shows that ${𝒞}^1$-smoothness is not sufficient.

In the paper we consider lower semicontinuous differential inclusions with one sided Lipschitz and compact valued right hand side in a Banach space with uniformly convex dual. We examine the nonemptiness and some qualitative properties of the solution set.

Some properties of differential inclusions with lower semicontinuous right-hand side are considered. Our essential assumption is the one-sided Lipschitz condition introduced in [4]. Using the main idea of [10], we extend the well known relaxation theorem, stating that the solution set of the original problem is dense in the solution set of the relaxed one, under assumptions essentially weaker than those in the literature. Applications in optimal control are given.