Distributed formation control of multiple unmanned aerial vehicles over time-varying graphs using population games

© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This paper presents a control technique based on distributed population dynamics under time-varying communication graphs for a multi-agent system structured in a leader-follower fashion. Here, the leader agent follows a particular trajectory and the follower agents should track it in a certain organized formation manner. The tracking of the leader can be performed in the position coordinates x; y; and z, and in the yaw angle phi. Additional features are performed with this method: each agent has only partial knowledge of the position of other agents and not necessarily all agents should communicate to the leader. Moreover, it is possible to integrate a new agent into the formation (or for an agent to leave the formation task) in a dynamical manner. In addition, the formation configuration can be changed along the time, and the distributed population-games-based controller achieves the new organization goal accommodating conveniently the information-sharing graph in function of the communication range capabilities of each UAV. Finally, several simulations are presented to illustrate different scenarios, e.g., formation with time-varying communication network, and time-varying formationPeer ReviewedPostprint (author's final draft

Distributed MPC with time-varying communication network: A density-dependent population games approach

© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This work addresses distributed control design by using density-dependent population dynamics. Furthermore, stability of the equilibrium point under this proposed class of population dynamics is studied, and the relationship between the equilibrium point of density-dependent population games (DDPG) and the solution of constrained optimization problems is shown. Finally, a distributed predictive control is designed with the proposed density-dependent dynamics, and contemplating a time-varying communication network.Peer ReviewedPostprint (author's final draft

Non-centralized Control for Flow-based Distribution Networks: A Game-theoretical Insight

This paper solves a data-driven control problem for a flow-based distribution network with two objectives: a resource allocation and a fair distribution of costs. These objectives represent both cooperation and competition directions. It is proposed a solution that combines either a centralized or distributed cooperative game approach using the Shapley value to determine a proper partitioning of the system and a fair communication cost distribution. On the other hand, a decentralized noncooperative game approach computing the Nash equilibrium is used to achieve the control objective of the resource allocation under a non-complete information topology. Furthermore, an invariant-set property is presented and the closed-loop system stability is analyzed for the non cooperative game approach. Another contribution regarding the cooperative game approach is an alternative way to compute the Shapley value for the proposed specific characteristic function. Unlike the classical cooperative-games approach, which has a limited application due to the combinatorial explosion issues, the alternative method allows calculating the Shapley value in polynomial time and hence can be applied to large-scale problems.Generalitat de Catalunya FI 2014Ministerio de Ciencia y Educación DPI2016-76493-C3-3-RMinisterio de Ciencia y Educación DPI2008-05818Proyecto europeo FP7-ICT DYMASO

On the modeling and real-time control of urban drainage systems: A survey

Trabajo presentado a la 11th International Conference on Hydroinformatics celebrada en New York (US) del 17 al 21 de agosto de 2014.Drainage networks are complex systems composed by several processes including recollection, transport, storing, treatment, and releasing the water to a receiving environment. The way Urban Drainage Systems (UDS) manage wastewater is through the convenient handling of active elements such as gates (redirection and/or retention), storing tanks, and pumping stations, when needed. Therefore, modeling and control of UDS basically consists in knowing and representing the (dynamical) behavior of these elements and managing them properly in order to achieve a given set of control objectives, such as minimization of flooding in streets or maximization of treated wastewater in the system. Given the large number of elements composing an UDS and the interaction between them, management and control strategies may depend on highly complex system models, which implies the explicit difficulty for designing real-time control (RTC) strategies. This paper makes a review of the models used to describe, simulate, and control UDS, proposes a revision of the techniques and strategies commonly used for the control UDS, and finally compares several control strategies based on a case study.This work has been partially supported by project N°548-2012 “Drenaje Urbano y Cambio Climático: Hacia los Sistemas de Alcantarillado del Futuro.”, Mexichem Colombia S.A, the scholarships of Colciencias N°567-2012 and 647-2013, and the EU Project EFFINET (FP7-ICT-2011-8-31855) and the DGR of Generalitat de Catalunya (SAC group Ref. 2009/SGR/1491).Peer Reviewe

On The Modeling And Real-Time Control Of Urban Drainage Systems: A Survey

Drainage network are complex systems composed by several processes including recollection, transport, storing, wastewater and/or rain treatment, and return of the water to a receiving environment. Urban drainage systems (UDS) involve most of these processes inside cities and can be either separate or combined systems, depending on how wastewater and rainwater are managed. The way UDS manage the wastewater is through the convenient handling of active elements such as gates (redirection and/or retention), storing tanks and pumping stations, when needed. Therefore, the modeling and control of UDS basically consists in knowing and representing the (dynamical) behavior of those elements and manage them properly in order to achieve a given set of control objectives, such as minimization of flooding in streets or maximization of treated wastewater in the system. Given the large number of elements composing a UDS and the interaction between them, management and control strategies may depend on highly complex system models, what implies the explicit difficulty for designing real-time control strategies. This paper makes a review on the huge world of models used to describe, simulate, and control UDS. Moreover, a revision of the techniques and strategies commonly used for the control of these systems is also presented and discussed. Mechanisms that ensure the correct operation of the UDS under presence of failures or communication flaws in the system are considered as well

On the modeling and real-time control of urban drainage systems: A survey

Drainage networks are complex systems composed by several processes including recollection, transport, storing, treatment, and releasing the water to a receiving environment. The way Urban Drainage Systems (UDS) manage wastewater is through the convenient handling of active elements such as gates (redirection and/or retention), storing tanks, and pumping stations, when needed. Therefore, modeling and control of UDS basically consists in knowing and representing the (dynamical) behavior of these elements and managing them properly in order to achieve a given set of control objectives, such as minimization of flooding in streets or maximization of treated wastewater in the system. Given the large number of elements composing an UDS and the interaction between them, management and control strategies may depend on highly complex system models, which implies the explicit difficulty for designing real-time control (RTC) strategies. This paper makes a review of the models used to describe, simulate, and control UDS, proposes a revision of the techniques and strategies commonly used for the control UDS, and finally compares several control strategies based on a case study.Peer ReviewedPostprint (author’s final draft

A class of population dynamics for reaching epsilon-equilibria : engineering applications

© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksThis document proposes a novel class of population dynamics that are parameterized by a nonnegative scalar . We show that any rest point of the proposed dynamics corresponds to an -equilibrium of the underlying population game. In order to derive this class of population dynamics, our approach is twofold. First, we use an extension of the pairwise comparison revision protocol and the classic mean dynamics for well-mixed populations. This approach requires full-information. Second, we employ the same revision protocol and a version of the mean dynamics for non-well-mixed populations that uses only local information. Furthermore, invariance properties of the set of allowed population states are analyzed, and stability of the -equilibria is formally proven. Finally, two engineering examples based on the -dynamics are presented: A control scenario in which noisy measurements should be mitigated, and a humanitarian engineering application related to wealth distribution in poor societies. © 2016 American Automatic Control Council (AACC).Peer ReviewedPostprint (author's final draft