AN OPTIMIZATION ALGORITHM FOR THE COORDINATED HYBRID AGENT FRAMEWORK

H. Li, F. Karray, and O. Basir

Keywords

Multiagent systems, hybrid control systems, framework, optimization

Abstract

The Coordinated Hybrid Agent (CHA) framework for the control of Multi-Agent Systems (MASs) has been used to model both homogeneous and heterogeneous MASs. In this framework, the control of MASs is considered as decentralized control and coordination of agents. The CHA framework models hybrid systems with both continuous and discrete dynamics, and both deliberative control and reactive control. The CHA framework is able to model coordination tasks for MASs. Recently, the optimization problem for a CHA system has been formulated. In this study, the optimization of MASs modelled by the CHA framework is studied. The optimization of a CHA system can be described by using time-driven and event-driven dynamics. Because the system is modelled as a combination of timedriven and event-driven dynamics, the optimization algorithms have to address both issues at the same time. The optimization problem of a heterogeneous Multi-Agent System (MAS) modelled using the CHA framework is analysed. A direct identification algorithm is proposed to optimize the performance and time of the MAS. For each single agent modelled using the CHA framework, the direct identification algorithm is applied to solve the optimization problem. The idea is that we can identify the busy period structure of an agent by optimizing all busy periods. Through the application of the proposed direct identification algorithm to the optimization of MASs, we are able to achieve optimized coordinated control of heterogeneous MASs. Simulation and experimental results demonstrate the efficiency of the proposed optimization algorithm.

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