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Model Reference Adaptive Stabilizing Control with Application to Leaderless Consensus

Yue, Dongdong (author), Baldi, S. (author), Cao, Jinde (author), De Schutter, B.H.K. (author)

This article describes an extension of the well-known model reference adaptive control (MRAC) approach. The extension relies on explicitly involving the tracking error in the feedback control law: it is shown that including this term along with its appropriate extra adaptive gain allows one to handle possibly unstable reference dynamics....

journal article 2024

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Airline Network Planning Considering Climate Impact: Assessing New Operational Improvements

Noorafza, M. (author), Santos, Bruno F. (author), Sharpanskykh, Alexei (author), Zengerling, Zarah L. (author), Weder, Christian M. (author), Linke, Florian (author), Grewe, V. (author)

The aviation industry has set an ambitious goal of reducing its climate impacts. Accordingly, airlines must balance their plans according to this goal with financial considerations. We developed a multi-objective framework to facilitate climate-aware network design by incorporating the objective to minimise the flight average temperature...

journal article 2023

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A Coalitional MPC Approach to Control of Collaborative Vehicle Platoons

Chanfreut, P. (author), Keijzer, T. (author), Maestre, J. M. (author), Ferrari, Riccardo M.G. (author)

This work presents a coalitional model predictive controller for collaborative vehicle platoons. The overall system is modeled as a string of locally controlled vehicles that can share data through a wireless communication network. The vehicles can dynamically form disjoint groups that coordinate their actions, i.e., the so-called coalitions....

journal article 2023

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Optimal Selection and Tracking of Generalized Nash Equilibria in Monotone Games

Benenati, E. (author), Ananduta, W. (author), Grammatico, S. (author)

A fundamental open problem in monotone game theory is the computation of a specific generalized Nash equilibrium (GNE) among all the available ones, e.g. the optimal equilibrium with respect to a system-level objective. The existing GNE seeking algorithms have in fact convergence guarantees toward an arbitrary, possibly inefficient,...

journal article 2023

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Semi-Decentralized Generalized Nash Equilibrium Seeking in Monotone Aggregative Games

Belgioioso, Giuseppe (author), Grammatico, S. (author)

We address the generalized Nash equilibrium seeking problem for a population of agents playing aggregative games with affine coupling constraints. We focus on semi-decentralized communication architectures, where there is a central coordinator able to gather and broadcast signals of aggregative nature to the agents. By exploiting the...

journal article 2023

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Bilateral Peer-to-Peer Energy Trading via Coalitional Games

Raja, A.A. (author), Grammatico, S. (author)

In this article, we propose a bilateral peer-to-peer (P2P) energy trading scheme under single-contract and multi-contract market setups, both as an assignment game, a special class of coalitional games. The proposed market formulation allows for efficient computation of a market equilibrium while keeping the desired economic properties...

journal article 2023

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Learning generalized Nash equilibria in monotone games: A hybrid adaptive extremum seeking control approach

Krilašević, S. (author), Grammatico, S. (author)

In this paper, we solve the problem of learning a generalized Nash equilibrium (GNE) in merely monotone games. First, we propose a novel continuous semi-decentralized solution algorithm without projections that uses first-order information to compute a GNE with a central coordinator. As the second main contribution, we design a gain...

journal article 2023

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Distributed Adaptive Optimization with Weight-Balancing

Yue, D. (author), Baldi, S. (author), Cao, Jinde (author), De Schutter, B.H.K. (author)

This article addresses the continuous-time distributed optimization of a strictly convex summation-separable cost function with possibly nonconvex local functions over strongly connected digraphs. Distributed optimization methods in the literature require convexity of local functions, or balanced weights, or vanishing step sizes, or algebraic...

journal article 2022

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Payoff distribution in robust coalitional games on time-varying networks

Raja, A.A. (author), Grammatico, S. (author)

In this article, we consider a sequence of transferable utility coalitional games, where the actual coalitional values are unknown but vary within known bounds. As a solution to the resulting family of games, we formalize the notion of 'robust core.' Our main contribution is to design two distributed algorithms, namely 1) distributed payoff...

journal article 2022

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Distributed Time-Varying Optimization of Second-Order Multiagent Systems Under Limited Interaction Ranges

Hong, Huifen (author), Baldi, S. (author), Yu, Wenwu (author), Yu, Xinghuo (author)

This article investigates the distributed time-varying optimization problem for second-order multiagent systems (MASs) under limited interaction ranges. The goal is to seek the minimum of the sum of local time-varying cost functions (CFs), where each CF is only available to the corresponding agent. Limited communication range refers to the...

journal article 2022

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Fast generalized Nash equilibrium seeking under partial-decision information

Bianchi, M. (author), Belgioioso, Giuseppe (author), Grammatico, S. (author)

We address the generalized Nash equilibrium seeking problem in a partial-decision information scenario, where each agent can only exchange information with some neighbors, although its cost function possibly depends on the strategies of all agents. The few existing methods build on projected pseudo-gradient dynamics, and require either double...

journal article 2022

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Stochastic generalized Nash equilibrium seeking under partial-decision information

Franci, B. (author), Grammatico, S. (author)

We consider for the first time a stochastic generalized Nash equilibrium problem, i.e., with expected-value cost functions and joint feasibility constraints, under partial-decision information, meaning that the agents communicate only with some trusted neighbors. We propose several distributed algorithms for network games and aggregative...

journal article 2022

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Large-scale collaborative vehicle routing

Los, J. (author), Schulte, F. (author), Gansterer, Margaretha (author), Hartl, Richard F. (author), Spaan, M.T.J. (author), Negenborn, R.R. (author)

Carriers can remarkably reduce transportation costs and emissions when they collaborate, for example through a platform. Such gains, however, have only been investigated for relatively small problem instances with low numbers of carriers. We develop auction-based methods for large-scale dynamic collaborative pickup and delivery problems,...

journal article 2022

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Actor-critic reinforcement learning for bidding in bilateral negotiation

Arslan, Furkan (author), Aydoğan, Reyhan (author)

Designing an effective and intelligent bidding strategy is one of the most compelling research challenges in automated negotiation, where software agents negotiate with each other to find a mutual agreement when there is a conflict of interests. Instead of designing a hand-crafted decision-making module, this work proposes a novel bidding...

journal article 2022

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A Directed Spanning Tree Adaptive Control Solution to Time-Varying Formations

Yue, D. (author), Baldi, S. (author), Cao, Jinde (author), Li, Qi (author), De Schutter, B.H.K. (author)

In this article, the time-varying formation and time-varying formation tracking problems are solved for linear multiagent systems over digraphs without the knowledge of the eigenvalues of the Laplacian matrix associated with the digraph. The solution to these problems relies on an approach that generalizes the directed spanning tree (DST)...

journal article 2021

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Analysing factorizations of action-value networks for cooperative multi-agent reinforcement learning

Castellini, Jacopo (author), Oliehoek, F.A. (author), Savani, Rahul (author), Whiteson, Shimon (author)

Recent years have seen the application of deep reinforcement learning techniques to cooperative multi-agent systems, with great empirical success. However, given the lack of theoretical insight, it remains unclear what the employed neural networks are learning, or how we should enhance their learning power to address the problems on which...

journal article 2021

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Learning generalized Nash equilibria in multi-agent dynamical systems via extremum seeking control

Krilašević, S. (author), Grammatico, S. (author)

In this paper, we consider the problem of learning a generalized Nash equilibrium (GNE) in strongly monotone games. First, we propose semi-decentralized and distributed continuous-time solution algorithms that use regular projections and first-order information to compute a GNE with and without a central coordinator. As the second main...

journal article 2021

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An integral nash equilibrium control scheme for a class of multi-agent linear systems

Krilašević, S. (author), Grammatico, S. (author)

We propose an integral Nash equilibrium seeking control (I-NESC) law which steers the multi-agent system composed of a special class of linear agents to the neighborhood of the Nash equilibrium in noncooperative strongly monotone games. First, we prove that there exist parameters of the integral controller such that the system converges to...

journal article 2021

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Continuous-time fully distributed generalized Nash equilibrium seeking for multi-integrator agents

Bianchi, M. (author), Grammatico, S. (author)

We consider strongly monotone games with convex separable coupling constraints, played by dynamical agents, in a partial-decision information scenario. We start by designing continuous-time fully distributed feedback controllers, based on consensus and primal–dual gradient dynamics, to seek a generalized Nash equilibrium in networks of single...

journal article 2021

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Consensus in high-power multiagent systems with mixed unknown control directions via hybrid Nussbaum-based control

Lv, Maolong (author), Yu, Wenwu (author), Cao, Jinde (author), Baldi, S. (author)

This work investigates the consensus tracking problem for high-power nonlinear multiagent systems with partially unknown control directions. The main challenge of considering such dynamics lies in the fact that their linearized dynamics contain uncontrollable modes, making the standard backstepping technique fail; also, the presence of mixed...

journal article 2020