An analytical H2 controller design approach of homogeneous multi-agent systems with time delays is presented to improve consensus performance. Firstly, a closed-loop multi-input multi-output framework in frequency domain is introduced, and a consensus tracking condition is given. Secondly, the decomposition method is utilized to simplify the analysis of internal stability and H2 performance index of the whole system to a set of independent optimization problems. Finally, the H2 optimal controller can be computed from all the stabilizing controllers. The contributions of the new approach are that the design procedure is conducted analytically for arbitrary delayed multi-agent systems, and a simple quantitative tuning way is developed to trade off the nominal performance and robustness. The simulation examples show the effectiveness of the proposed control strategy.
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http://dx.doi.org/10.1016/j.isatra.2016.09.016 | DOI Listing |
ISA Trans
January 2025
Department of Electrical Engineering, Shahid Bahonar University of Kerman, Kerman, Iran. Electronic address:
This paper introduces a fully distributed model-free adaptive control (MFAC) approach for consensus tracking in multi-agent systems (MASs) with compact form data linearization (CFDL). Unlike prior methods that require agents to know the full communication graph, our approach allows each agent to configure its controller using only local information from its neighbors, achieving a fully distributed control. Therefore, our method easily supports scenarios where agents dynamically join or leave MAS.
View Article and Find Full Text PDFEntropy (Basel)
December 2024
School of Computer Science, Peking University, Beijing 100871, China.
Multi-agent systems often face challenges such as elevated communication demands, intricate interactions, and difficulties in transferability. To address the issues of complex information interaction and model scalability, we propose an innovative hierarchical graph attention actor-critic reinforcement learning method. This method naturally models the interactions within a multi-agent system as a graph, employing hierarchical graph attention to capture the complex cooperative and competitive relationships among agents, thereby enhancing their adaptability to dynamic environments.
View Article and Find Full Text PDFISA Trans
January 2025
College of Mechanical and Vehicle Engineering, Hunan University, Changsha, 410082, Hunan, China. Electronic address:
Approximation-free control effectively addresses uncertainty and disturbances without relying on approximation techniques such as fuzzy logic systems (FLS) and neural networks (NNs). However, singularity problems-where signals exceed preset boundaries under dynamic operating conditions-remain a challenge. This paper proposes an improved approximation-free control (I-AFC) method for the multi-agent system, which introduces a novel singularity compensator, providing a low-complexity design with exceptional adaptability while reducing the risk of singularity issues under changing working conditions (random initial values, system parameter variations, and changes in topology graph and followers' dynamics).
View Article and Find Full Text PDFJ Biomed Inform
January 2025
ITMO University, Saint Petersburg, Russia. Electronic address:
The optimization in the ambulance dispatching process is significant for patients who need early treatments. However, the problem of dynamic ambulance redeployment for destination hospital selection has rarely been investigated. The paper proposes an approach to model and simulate the ambulance dispatching process in multi-agent healthcare environments of large cities.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Medical Information Department, Civil Hospices of Lyon, Lyon, France.
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