论文标题
分布式自适应控制：用于管理机器人回收厂的理想认知建筑候选者
Distributed Adaptive Control: An ideal Cognitive Architecture candidate for managing a robotic recycling plant
论文作者
论文摘要
在过去的十年中，社会在各种技术领域都经历了显着的增长。但是，尚未接受第四次工业革命。工业4.0构成了几个挑战，其中包括需要新的建筑模型来解决开放环境代表网络物理系统（CPS）的不确定性。废物电气和电子设备（WEEE）回收厂代表这样的开放环境之一。在这里，CPS必须在不断变化的环境中和谐地工作，与类似且不那么相似的CPS互动，并与人类工人进行适应合作。在本文中，我们支持分布式自适应控制（DAC）理论，作为用于管理回收植物的合适认知架构。具体而言，提出了DAC的递归实施（单一代理和大规模级别之间），以满足欧洲项目HR-Recycler的预期需求。此外，为了建立现实的基准，用于将来的递归DAC实施，提出了微型循环植物原型。
In the past decade, society has experienced notable growth in a variety of technological areas. However, the Fourth Industrial Revolution has not been embraced yet. Industry 4.0 imposes several challenges which include the necessity of new architectural models to tackle the uncertainty that open environments represent to cyber-physical systems (CPS). Waste Electrical and Electronic Equipment (WEEE) recycling plants stand for one of such open environments. Here, CPSs must work harmoniously in a changing environment, interacting with similar and not so similar CPSs, and adaptively collaborating with human workers. In this paper, we support the Distributed Adaptive Control (DAC) theory as a suitable Cognitive Architecture for managing a recycling plant. Specifically, a recursive implementation of DAC (between both single-agent and large-scale levels) is proposed to meet the expected demands of the European Project HR-Recycler. Additionally, with the aim of having a realistic benchmark for future implementations of the recursive DAC, a micro-recycling plant prototype is presented.
