Dissertation/ Thesis
On the design of optimization-based controllers via generalized nash equilibrium seeking in evolutionary games over networks
| Τίτλος: | On the design of optimization-based controllers via generalized nash equilibrium seeking in evolutionary games over networks |
|---|---|
| Συγγραφείς: | Martínez Piazuelo, Juan Pablo |
| Thesis Advisors: | Ocampo-Martínez, Carlos, Quijano Silva, Nicanor, Institut de Robòtica i Informàtica Industrial |
| Πηγή: | TDX (Tesis Doctorals en Xarxa) |
| Στοιχεία εκδότη: | Universitat Politècnica de Catalunya, 2024. |
| Έτος έκδοσης: | 2024 |
| Φυσική περιγραφή: | 213 p. |
| Θεματικοί όροι: | non-cooperative game theory, evolutionary game theory, population games, generalized Nash equilibria, evolutionary dynamics models, payoff dynamics models, distributed optimization-based control, large-scale complex systems, teoría de juegos no cooperativos, teroría de juegos evolutivos, juegos poblacionales, equilibrios generalizados de Nash, modelos de dinámicas evolutivas, modelos de dinámicas de pagos, control basado en optimización distribuida, sistemas complejos de gran escala, teoria de jocs no cooperatius, teoria de jocs evolutius, jocs poblacionals, equilibri generalitzat de Nash, model de dinàmiques evolutives, model de dinàmica de pagaments, control basat en l’optimització distribuïda, sistemes complexos a gran escala, Àrees temàtiques de la UPC::Informàtica, 68 - Industrias, oficios y comercio de artículos acabados. Tecnología cibernética y automática, 004 - Informàtica |
| Περιγραφή: | Tesi amb menció de Doctorat Internacional |
| Description (Translated): | (English) This doctoral thesis explores the utilization of generalized Nash equilibrium (GNE) seeking methods for evolutionary games over networks in designing optimization-based controllers for large-scale complex systems (LSCSs). The focus lies on population games, modeling strategic interactions among large populations of agents with bounded rationality. These games are deemed suitable for modeling large-scale optimization-based control problems either directly or by employing evolutionary dynamics models (EDMs) to update optimization variables. The concept of GNE emerges as a fitting solution for non-cooperative optimization-based control scenarios, where multiple subsystems maximize their utilities subject to coupling constraints. Consequently, this thesis frames optimization-based control as a GNE seeking problem and introduces novel game-theoretical methods for achieving GNEs in population games over networks. Applications in congestion games, charging coordination of plug-in electric vehicles (PEVs), dynamic resource allocation in solar collector fields, and residential demand response are discussed. The first part focuses on GNE seeking methods for population games under full information schemes, where non-local information estimation is not explicitly modeled. Two approaches are proposed: one dealing with capacity-constrained population games, introducing novel strategy revision protocols to ensure capacity constraint satisfaction, and another addressing population games with affine equality and convex inequality constraints, devising a payoff dynamics model (PDM) steering agents towards GNEs. Formal asymptotic stability guarantees are provided, and these methods are applied to design controllers for dynamic resource allocation in LSCSs. In contrast, the second part formulates GNE seeking methods for population games under partial information schemes, explicitly modeling non-local decision information estimation. It tackles reaching Nash equilibria without coupling constraints and achieving GNEs with affine equality constraints coupling multiple agents' decisions. Novel PDMs are formulated to estimate non-local information and compute dual Lagrange multipliers associated with coupling constraints. Asymptotic stability guarantees are provided, and the methods are applied to large-scale congestion games. The third part introduces hybrid PDMs combining continuous and discrete-time dynamics. Two event-triggered PDMs are devised to accommodate practical control features like logic implications and occasional communication. One mechanism focuses on PEV charging coordination, considering charging completion and random arrivals/departures of PEVs, while another aims to reduce communication costs in residential demand response. Formal convergence guarantees towards GNEs are deduced for both cases. In summary, this thesis contributes theoretically and practically to GNE seeking methods for population games over networks and to the design of optimization-based control strategies for LSCSs. DOCTORAT EN AUTOMÀTICA, ROBÒTICA I VISIÓ (Pla 2013) |
| Τύπος εγγράφου: | Dissertation/Thesis |
| Περιγραφή αρχείου: | application/pdf |
| Γλώσσα: | English |
| DOI: | 10.5821/dissertation-2117-452510 |
| Σύνδεσμος πρόσβασης: | https://hdl.handle.net/10803/696561 https://dx.doi.org/10.5821/dissertation-2117-452510 |
| Rights: | ADVERTIMENT. Tots els drets reservats. L'accés als continguts d'aquesta tesi doctoral i la seva utilització ha de respectar els drets de la persona autora. Pot ser utilitzada per a consulta o estudi personal, així com en activitats o materials d'investigació i docència en els termes establerts a l'art. 32 del Text Refós de la Llei de Propietat Intel·lectual (RDL 1/1996). Per altres utilitzacions es requereix l'autorització prèvia i expressa de la persona autora. En qualsevol cas, en la utilització dels seus continguts caldrà indicar de forma clara el nom i cognoms de la persona autora i el títol de la tesi doctoral. No s'autoritza la seva reproducció o altres formes d'explotació efectuades amb finalitats de lucre ni la seva comunicació pública des d'un lloc aliè al servei TDX. Tampoc s'autoritza la presentació del seu contingut en una finestra o marc aliè a TDX (framing). Aquesta reserva de drets afecta tant als continguts de la tesi com als seus resums i índexs. |
| Αριθμός Καταχώρησης: | edstdx.10803.696561 |
| Βάση Δεδομένων: | TDX |
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