Model-Based Development of Knowledge-Driven Self-Reconfigurable Machine Control Systems

To accommodate the trend toward mass customization launched by intelligent manufacturing in the era of Industry 4.0, this paper proposes the combination of model-driven engineering and knowledgedriven engineering during the development process of self-reconfigurable machine control systems. The complete tool chain for model development, execution, and reconfiguration is established. For the design phase, a machine-control-domain-specific modeling language and the supporting design environment are developed. With regard to the execution stage, a runtime framework compliant with the IEC 61499 standard is proposed. On the ground of the modeling environment and the reconfigurable run-time framework, a self-adaptive control module is developed to establish the close-loop self-reconfiguration infrastructure. The ontological representation of knowledge base toward this end is described, along with extendable SQWRL rules specified to automatically initiate the reconfiguration process in the cases of external user demands and internal faults. A prototype motion control kernel in the low-level layer of machine control system architecture is developed with the proposed modeling language and is then deployed to the runtime framework. Two case studies on self-reconfiguration of the proof-of-concept motion control kernel are demonstrated, which prove the feasibility of our proposal.