When users access shared resources in a selfish manner, the resulting societal cost and perceived users' cost is often higher than what would result from a centrally coordinated optimal allocation. While several contributions in mechanism design manage to steer the aggregate users choices to the desired optimum by using monetary tolls, such approaches bear the inherent drawback of discriminating against users with a lower income. More recently, incentive schemes based on artificial currencies have been studied with the goal of achieving a system-optimal resource allocation that is also fair. In this resource-sharing context, this paper focuses on repeated weighted congestion game with two resources, where users contribute to the congestion to different extents that are captured by individual weights. First, we address the broad concept of fairness by providing a rigorous mathematical characterization of the distinct societal metrics of equity and equality, i.e., the concepts of providing equal outcomes and equal opportunities, respectively. Second, we devise weight-dependent and time-invariant optimal pricing policies to maximize equity and equality, and prove convergence of the aggregate user choices to the system-optimum. In our framework it is always possible to achieve system-optimal allocations with perfect equity, while the maximum equality that can be reached may not be perfect, which is also shown via numerical simulations.

@inproceedings{PedrosoAgazziEtAl2024EqtEql,
author = {Leonardo Pedroso and Andrea Agazzi and W. P. M. H. Heemels and Mauro Salazar},
title = {Fair Artificial Currency Incentives in Repeated Weighted Congestion Games: Equity vs. Equality},
booktitle = {63nd IEEE Conference on Decision and Control},
year = {2024},
doi = {10.48550/arXiv.2403.03999},
note = {in press}
}

The implementation feasibility of control algorithms over very large-scale networks calls for hard constraints regarding communication, computational, and memory requirements. In this paper, the decentralized receding horizon control problem for very large-scale networks of dynamically decoupled systems with a common, possibly time-varying, control objective is addressed. Each system is assumed to be modeled by linear time-varying dynamics, which can be leveraged to approximate nonlinear systems about successive points of operation. A distributed and decentralized receding horizon control solution is put forward, which: (i) takes communication delays into account; (ii) allows local communication exclusively; and (iii) whose computational and memory requirements in each computational unit do not scale with the dimension of the network. The scalability of the proposed solution enables emerging very large-scale applications of swarm robotics and networked control. This approach is applied to the orbit control problem of low Earth orbit mega-constellations, featuring high-fidelity numerical simulations for the Starlink mega-constellation.

@article{PedrosoBatista2023DistributedRHC,
author = {Leonardo Pedroso and Pedro Batista},
title = {Distributed decentralized receding horizon control for very large-scale networks with application to satellite mega-constellations},
journal = {Control Engineering Practice},
year = {2023},
volume = {141},
pages = {105728},
doi = {10.1016/j.conengprac.2023.105728}
}

The major hurdle in accessing laboratory experimentation is the cost of acquiring experimental scientific equipment, which is unbearable for many institutions. This paper aims to provide the community of control educators, practitioners, and researchers with an open-source low-cost experimental setup and dedicated interface, which is flexible and very easily reproducible. The proposed apparatus is a setup of four interconnected tanks. The setup is representative of real-life industrial processes and it can be adjusted to allow for several configurations for flexibility. A user-friendly dedicated MATLAB/Simulink interface with a personal computer is developed. It supports a seamless shift between a numeric simulation of the quadruple-tank process dynamics and the interface with the physical experimental plant. The CAD models, technical drawings, wiring schematics, PCB design, interface, assembly tutorials, and several examples are provided in an open-source repository. The parts are inexpensive, readily obtained, and fast to assemble. Each setup costs under 650€ and takes roughly 4 h to assemble. In this paper, several application examples are presented, not only for educational purposes, but also for the validation of a state-of-the-art decentralized control method.

@article{PedrosoBatista2022Quadruple-tank,
author = {Leonardo Pedroso and Pedro Batista},
title = {Reproducible low-cost flexible quadruple-tank process experimental setup for control educators, practitioners, and researchers},
journal = {Journal of Process Control},
year = {2022},
volume = {118},
pages = {82-94},
doi = {10.1016/j.jprocont.2022.08.010}
}

Signal control strategies for congested urban road networks designed in a centralized framework require many communication links, serious processing power, and infrastructure for the centralized coordination. As a result, strategies based on a centralized framework are not scalable. The use of decentralized signal control strategies for large-scale urban traffic networks is a solution to this problem, since it allows for the implementation of such strategies on networks whose centralized solution is not easily scalable. This paper addresses the problem of designing a decentralized traffic-responsive signal control solution, proposing two methods based on different formulations of the store-and-forward model: (i) the Decentralized Traffic-responsive Urban Control (DTUC) method; and (ii) the Decentralized Decoupled Traffic-responsive Urban Control (D2TUC). The decentralized configuration is such that each intersection is associated with one computational unit, with limited computational power and memory, which controls the traffic signals of the incoming links. Sufficient conditions for the controllability of the considered store-and-forward models are also presented. Both methods are validated resorting to numerical simulations of the urban traffic network of Chania, Greece, for two demand scenarios, and their performance is compared with the performance of the Traffic-responsive Urban Control (TUC) centralized strategy. One of the proposed decentralized methods, D2TUC, is shown to match the performance of TUC.

@article{PedrosoBatista2021SignalControl,
author = {Leonardo Pedroso and Pedro Batista},
title = {Decentralized store-and-forward based strategies for the signal control problem in large-scale congested urban road networks},
journal = {Transportation Research Part C: Emerging Technologies},
year = {2021},
volume = {132},
pages = {103412},
doi = {10.1016/j.trc.2021.103412}
}