Hierarchical distributed model predictive control based on fuzzy negotiation

•More flexible controller tuning is achieved combining DMPC and fuzzy approaches.•The control scheme provides scalability and ease of deployment in multi-agent systems.•Feasibility and stability are guaranteed for the proposed control method.•Various tuning parameters are considered to study the inf...

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Bibliographic Details
Published in:Expert systems with applications 2021-08, Vol.176, p.114836, Article 114836
Main Authors: Masero, Eva, Francisco, Mario, Maestre, José M., Revollar, Silvana, Vega, Pastora
Format: Article
Language:English
Subjects:
Algorithms
Control algorithms
Control stability
Control theory
Coupling
Couplings
Feedback control
Fuzzy control
Fuzzy logic
Hierarchical distributed control
Model predictive control
Multi-agent systems
Multiagent systems
Negotiations
Pairwise negotiations
Predictive control
Stability
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Summary:•More flexible controller tuning is achieved combining DMPC and fuzzy approaches.•The control scheme provides scalability and ease of deployment in multi-agent systems.•Feasibility and stability are guaranteed for the proposed control method.•Various tuning parameters are considered to study the influence of fuzzy rules. This work presents a hierarchical distributed model predictive control approach for multiple agents with cooperative negotiations based on fuzzy inference. Specifically, a fuzzy-based two-layer control architecture is proposed. In the lower control layer, there are pairwise negotiations between agents according to the couplings and the communication network. The resulting pairwise control sequences are sent to a coordinator in the upper control layer, which merges them to compute the final ones. Furthermore, conditions to guarantee feasibility and stability in the closed-loop system are provided. The proposed control algorithm has been tested on an eight-coupled tank plant via simulation.
ISSN:0957-4174
1873-6793
DOI:10.1016/j.eswa.2021.114836