A Coalitional Control Scheme with Topology-Switchings Convexity Guarantees

Chanfreut, Paula; Maestre, J. M.; Muros, Francisco Javier; Camacho, Eduardo F.

doi:10.1109/cdc40024.2019.9030238

Cited by 8 publications

(15 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Nevertheless, fuzzy logic requires application knowledge and manual modifications to the process. Other approaches make use of game theory, e.g., of min-max games [10] and coali-tional games [11], [12]. These approaches, however, focus on coalitional approaches rather than cooperative approaches.…”

Section: B Related Workmentioning

confidence: 99%

Coordinated Cooperative Distributed Decision-Making Using Synchronization of Local Plans

Kloock

Alrifaee

2023

IEEE Trans. Intell. Veh.

View full text Add to dashboard Cite

In cooperative decision-making, agents locally plan for a subset of all agents. Due to only local system knowledge of the agents, these local plans are inconsistent to local plans of other agents. This inconsistency leads to infeasibility of the plans. This article introduces an algorithm for synchronizing local plans for cooperative distributed decision-making. The algorithm enables parallel decision-making and achieves feasible decisions. The algorithm consists of two iterative steps: local planning and global synchronization. In the local planning step, the agents parallely compute local decisions, referred to as plans. Subsequently, consistency of the local plans across agents is achieved using global synchronization. The globally synchronized plans act as reference decisions to the local planning step in the next iteration. In each iteration, the local planning guarantees locally feasible plans, while the synchronization guarantees globally consistent plans in that iteration. The parallel algorithm converges to globally feasible decisions if the coupling topology is feasible. We introduce requirements for the coupling topology to achieve convergence to globally feasible decisions and present the algorithm using a model predictive control example. Our evaluations with car-like robots show that globally feasible decisions are achieved.

show abstract

Section: B Related Workmentioning

confidence: 99%

Coordinated Cooperative Distributed Decision-Making Using Synchronization of Local Plans

Kloock

Alrifaee

2023

IEEE Trans. Intell. Veh.

View full text Add to dashboard Cite

show abstract

“…Other approaches make use of game theory, e.g., of min-max games [13] and coalitional games [14], [15].…”

Section: A Related Workmentioning

confidence: 99%

“…where α (k,i) is the transposed weighting factor resulting from Eq. (15). The agents communicate the locally averaged plans x (−) − (•) and iteratively perform local average steps and communicate the intermediate results to their neighbors until the plans are synchronized, i.e., x…”

Section: B Synchronization Of Plansmentioning

confidence: 99%

Coordinated Cooperative Distributed Decision-Making using Synchronization of Local Plans

Kloock¹,

Alrifaee²

2023

Preprint

View full text Add to dashboard Cite

In cooperative decision-making, agents locally plan for a subset of all agents. Due to only local system knowledge of the agents, these local plans may be inconsistent to local plans of other agents. This inconsistency leads to infeasibility of the plans. This article introduces an algorithm for synchronizing local plans for cooperative distributed decision-making of multi-agent systems. The algorithm consists of two iterative steps: planning and synchronization. In the local planning step, the agents compute local decisions, referred to as plans. Subsequently, consistency of the local plans across agents is achieved using synchronization. The synchronized plans act as reference decisions to the local planning step in the next iteration. In each iteration, the local planning guarantees locally feasible plans, while the synchronization guarantees globally consistent plans in that iteration. The algorithm converges to globally feasible decisions if the coupling topology is feasible. We introduce requirements for the coupling topology to achieve convergence to globally feasible decisions and present the algorithm using a model predictive control example. Our evaluations with car-like robots show that feasible decisions are achieved.

show abstract

“…In this paper the coalitional control scheme, with switching topologies, presented in Maestre et al (2014); Chanfreut et al (2019) is extended to a more general scenario, while keeping all the stability guarantees. Under this framework, the topology of the communication network is dynamically selected from a set of predefined alternatives.…”

Section: Main Contributionsmentioning

confidence: 99%

“…Notice that the introduction of variable Λ noticeably hinders the control problem. In previous work (Maestre et al, 2014;Chanfreut et al, 2019) the authors have found an approximate optimal solution to this problem using Linear Matrix Inequalities (LMIs), assuming the agents have perfect knowledge of their state. In this paper this assumption is removed and an alternative control and observation scheme is introduced, while still only requiring LMIs to be solved for a guaranteed stable design.…”

Section: Control Objectivementioning

confidence: 99%

A Topology-Switching Coalitional Control and Observation Scheme with Stability Guarantees

Chanfreut,

Keijzer,

Ferrari

et al. 2021

Preprint

View full text Add to dashboard Cite

In this paper a coalitional control and observation scheme is presented in which the coalitions are changed online by enabling and disabling communication links. Transitions between coalitions are made to best balance overall system performance and communication costs. Linear Matrix Inequalities are used to design the controller and observer, guaranteeing stability of the switching system. Simulation results for vehicle platoon control are presented to illustrate the proposed method.

show abstract

A Coalitional Control Scheme with Topology-Switchings Convexity Guarantees

Cited by 8 publications

References 16 publications

Coordinated Cooperative Distributed Decision-Making Using Synchronization of Local Plans

Coordinated Cooperative Distributed Decision-Making Using Synchronization of Local Plans

Coordinated Cooperative Distributed Decision-Making using Synchronization of Local Plans

A Topology-Switching Coalitional Control and Observation Scheme with Stability Guarantees

Contact Info

Product

Resources

About