Scalability of Cyber-Physical Systems with Real and Virtual Robots in ROS 2.

Nowadays, cyber-physical systems (CPSs) are composed of more and more agents and the demand for designers to develop ever larger multi-agent systems is a fact. When the number of agents increases, several challenges related to control or communication problems arise due to the lack of scalability of existing solutions. It is important to develop tools that allow control strategies evaluation of large-scale systems.

Periodic event-triggered targeted shape control of Lagrangian systems with discrete-time delays.

We study the problem of periodic event-triggered targeted formation control for multi-agent Lagrangian systems. We assume that the equations of motion of each agent are derived from a Lagrangian function. Besides, each agent has information about a predefined convex set as a targeted set.

High prognostic value of measurable residual disease detection by flow cytometry in chronic lymphocytic leukemia patients treated with front-line fludarabine, cyclophosphamide, and rituximab, followed by three years of rituximab maintenance.

It has been postulated that monitoring measurable residual disease (MRD) could be used as a surrogate marker of progression-free survival (PFS) in chronic lymphocytic leukemia (CLL) patients after treatment with immunochemotherapy regimens. In this study, we analyzed the outcome of 84 patients at 3 years of follow-up after first-line treatment with fludarabine, cyclophosphamide and rituximab (FCR) induction followed by 36 months of rituximab maintenance thearpy. MRD was assessed by a quantitative four-color flow cytometry panel with a sensitivity level of 10 Eighty out of 84 evaluable patients (95.

Optimal Control for Aperiodic Dual-Rate Systems With Time-Varying Delays.

In this work, we consider a dual-rate scenario with slow input and fast output. Our objective is the maximization of the decay rate of the system through the suitable choice of the -input signals between two measures (periodic sampling) and their times of application. The optimization algorithm is extended for time-varying delays in order to make possible its implementation in networked control systems.

Identification of process transfer function parameters in event-based PI control loops.

This paper presents a method to estimate the parameters of first and second order systems with time delays with different accuracy levels for autotuning of event-based PI control loops. In particular, the event-based sampling condition applied in this work is based on the sampling strategy known as symmetric-send-on-delta (SSOD). The method is based on forcing the system to enter into a limit cycle and on using the information achieved from the oscillation to estimate the transfer function parameters.