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Agent-based holonic design and operations environment for distributed manufacturing
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Supervision of adaptive fuzzy controllers for manufacturing systems
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Fuzzy Sets and Systems
On stability of fuzzy systems expressed by fuzzy rules with singleton consequents
IEEE Transactions on Fuzzy Systems
Nonlinear internal model control: application of inverse model based fuzzy control
IEEE Transactions on Fuzzy Systems
Inverse controller design for fuzzy interval systems
IEEE Transactions on Fuzzy Systems
An educational tool for fuzzy control
IEEE Transactions on Fuzzy Systems
MIN and MAX Operators for Fuzzy Intervals and Their Potential Use in Aggregation Operators
IEEE Transactions on Fuzzy Systems
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Automatica (Journal of IFAC)
Distributed control of production systems
Engineering Applications of Artificial Intelligence
ETFA'09 Proceedings of the 14th IEEE international conference on Emerging technologies & factory automation
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VECoS'11 Proceedings of the Fifth international conference on Verification and Evaluation of Computer and Communication Systems
Proceedings of the Winter Simulation Conference
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This paper deals with the development of an intelligent distributed and supervised control approach for high-volume production systems, in which the flow of parts can be approximated by a continuous (fluid) model. The proposed approach is based on the decomposition of the production system into elementary modules in order to reduce the control design computational complexity. In this context, a two levels control structure is proposed. At the local level, a surplus-based principle is adopted to regulate the production flow for each module according to the distributed structure. The proposed control methodology decides how to adjust the production rate in order to avoid system overloading and eliminate machine starvation or blocking. In this context, the local control law is synthesized by using the Takagi-Sugeno fuzzy systems. At the high level, a supervisory controller is designed to improve the overall system performances. A supervisor provides an additive component for each local controller when the overall system performances deviate from their acceptable domains (degraded mode). This is done by combining both local and global information into a unified formalism by using aggregation operators and according to fuzzy interval representation of the desired objectives. Finally, the feasibility of the proposed methodology is validated with simulation examples.