This paper investigates the on-line optimization of an existing petrochemical plant. The process consists of a train of two distillation columns where a group of n-paraffins is separated into kerosene and lights. Because of process heat integration and recycles, a significant interaction between both columns is observed, which makes very complex the adjustments of process operation to the chang...

Traffic management in large networks remains an important challenge in transportation systems. The best approach would be to use existing infrastructure and find a solution to manage the increasing flows of vehicles. Multi-agent systems and autonomous vehicles are today considered as a promising approach to deal with traffic control. In this paper, we propose a two-level decentralized multi-age...

Unprecedented high volumes of data are becoming available with the growth of the advanced metering infrastructure. These are expected to benefit planning and operation of the future power system, and to help the customers transition from a passive to an active role. In this paper, we explore for the first time in the smart grid context the benefits of using Deep Reinforcement Learning, a hybrid...

In this paper we propose several heuristic algorithms that, using MPLS capabilities, provide network operators with a control framework for the routing plane. In particular, a monitoring block collects real-time measurements, such as the link load, and feeds them to a centralized decision block which runs a routing optimization algorithm. The output of the optimization process is then conveyed ...

The filters tuning is a crucial issue due the need to quantify the accuracy of the model in terms of the process noise covariance matrix for process characterized by structural uncertainties which are time-varying. Thus, approaches to time-varying covariances were studied and included to a traditional EKF and an optimization-based state estimators constrained EKF (CEKF) formulations. The result...

In this paper, the on-line optimization of batch reactors under parametric uncertainty is considered. A method is presented that estimates the likely economic performance of the on-line optimizer. The nmthod of t)rthogonal collocation is employed to convert the differential algebraic optimization problem (DAOP) of the dynamic optinfization into a nonlinear t)rogram (NLP) and determine the nomin...

The paper demonstrates the place, role and mutual interaction of advanced control algorithms and on-line set-point optimization in process control structures. First, a multilayer control structure resulting from a functional decomposition is briefly presented. The role and selected realizations of advanced control algorithms, in particular mostly applied now model predictive control (MPC) ones,...

In this paper, we present an OSPF weights optimization scheme using a general automatic network management framework proposed in [1], i.e., on-line simulation framework. We have chosen the packet drop rate in the network as the optimization metric as it is a good indicator of congestion in the network and also impacts the performance of the underlying applications. The packet drop rate has been...

This paper discusses a number of discrete models used for optimization of cutting condition during NC machining. The models can be broadly placed into two categories: 1. volumetric models in which feedrate is proportional to either average or instantaneous volumetric removal rate, 2. vector force models in which feedrate is set to values which keep either average or instantaneous cutting forces...