# name
Distributed adaptive control: An ideal cognitive architecture candidate for managing a robotic recycling plant

# metadata.dc.description.abstract[].value
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.

# metadata.dc.relation.ispartof[].value
Lecture Notes In Computer Science, 2021, vol. 12413 LNAI, p. 153-164

# metadata.dc.relation.ispartof[].value
Biomimetic and Biohybrid Systems. 9th International Conference, Living Machines 2020, Freiburg, Germany, July 28–30, 2020, Proceedings

# metadata.dc.rights[].value
cc by (c) Guerrero Rosado, Oscar et al., 2020

# metadata.dc.source[].value
Comunicacions a congressos (Institut de Bioenginyeria de Catalunya (IBEC))

# metadata.dc.title[].value
Distributed adaptive control: An ideal cognitive architecture candidate for managing a robotic recycling plant