Nervousness in dynamic self-organized holonic multi-agent systems

Abstract

New production control paradigms, such as holonic and multi-agent systems, allow the development of more flexible and adaptive factories. In these distributed approaches, autonomous entities possess a partial view of the environment, being the decisions taken from the cooperation among them. The introduction of self-organization mechanisms to enhance the system adaptation may cause the system instability when trying to constantly adapt their behaviours, which can drive the system to fall into a chaotic behaviour. This paper proposes a nervousness control mechanism based on the classical Proportional, Integral and Derivative feedback loop controllers to support the system self-organization. The validation of the proposed model is made through the simulation of a flexible manufacturing system.