火电厂Multiagent控制系统中的优化任务分解Agents

Optimal Task Decomposition Agents of the Multiagent Power Plant Control System

提出了一个火电厂多代理控制系统(MACS),并详细介绍了其中优化任务分解代理子系统(OTDAS)的目标、决策和运行。OTDAS通过一个优化代理和一个分解代理对火电厂多代理控制系统的任务进行了优化分解。优化代理的决策采用了遗传算法(GA)。OTDAS的运行结果表明GA是Agent决策的有效工具。

This paper proposes optimal task decomposition agents （OTDAS） of the multiagent power plant control system （MACS）. The goal, decision-making and operation of the OTDAS are introduced respectively. The OTDAS optimally decompose the task of power plant control system through an optimizer agent and a decomposer agent. The optimizer agent makes decision using genetic algorithm （GA）. The operation results of OTDAS show that GA is an effective tool for the agent in making decision.