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Cristopher Hermosilla

Publications and source records attributed to Cristopher Hermosilla.

3 recordsLinked to original sources

On the Value Function of Convex Bolza Problems Governed by Stochastic Difference Equations

In this paper we study the value function of Bolza problems governed by stochastic difference equations, with particular emphasis on the convex non-anticipative case. Our goal is to provide some insights on the structure of the subdiferential of the value function. In particular, we establish a connection between the evolution of the subgradients of the value function and a stochastic difference equation of Hamiltonian type. This result can be seen as a transposition of the method of characteristics, introduced by Rockafellar and Wolenski in the 2000s, to the stochastic discrete-time setting. Similarly as done in the literature for the deterministic case, the analysis is based on a duality approach. For this reason we study first a dual representation for the value function in terms of the value function of a dual problem, which is a pseudo Bolza problem. The main difference with the deterministic case is that (due to the non-anticipativity) the symmetry between the Bolza problem and its dual is no longer valid. This in turn implies that ensuring the existence of minimizers for the Bolza problem (which is a key point for establishing the method of characteristics) is not as simple as in the deterministic case, and it should be addressed differently. To complete the exposition, we study the existence of minimizers for a particular class of Bolza problems governed by linear stochastic difference equations, the so-called linear-convex optimal control problems.

math.OC

Subgradient evolution of value functions in discrete-time optimal control

In this paper we investigate how the subgradients of the value function of a discrete-time convex Bolza problem evolve over time. In particular, we develop a discrete-time version of the characteristic method introduced by Rockafellar and Wolenski in the 2000s, by showing that the time-evolution of the subgradients of the value functions can be associated with trajectories of a discrete-time Hamiltonian system. To do so, we first prove that the value function has a dual counterpart, which corresponds to the conjugate of the value function of a suitable dual problem. We finally make a discussion about the qualification conditions we require for our results, showing in particular that classical problems, such as the Liner-Quadratic regulator, satisfy these hypotheses.

math.OC

On the set of robust sustainable thresholds for uncertain control systems

In natural resource management, or more generally in the study of sustainability issues, often the objective is to maintain the state of a given system within a desirable configuration, typically established in terms of standards or thresholds. For instance, in fisheries management, the procedure of designing policies may include keeping the spawning stock biomass over a critical threshold and also ensuring minimal catches. Given a controlled dynamical system in discrete-time, representing the evolution of some natural resources under the action of controls and uncertainties, and an initial endowment of the resources, the aim of this paper is to characterize the set of robust sustainable thresholds, that is, the thresholds for which there exists some control path, along with its corresponding state trajectory, satisfying for all possible uncertainty scenarios, prescribed mixed constraints parametrized by such thresholds. This set provides useful information to users and decision-makers, illustrating the trade-offs between constraints and it is strongly related to the robust viability, one of the key concepts in viability theory, discipline that study the consistency between a controlled dynamical system and given constraints. Specifically, we are concerned with characterizing the weak and strong Pareto fronts of the set of robust sustainable thresholds, providing a practical method for computing such objects based on optimal control theory and a level-set approach. A numerical example, relying on renewable resource management, is shown to demonstrate the proposed method.

math.OC