Parallel Cascade Decomposition for Supervisory Control of State-Tree Structures

Wang X, Li Z, Moor T (2026)

Publication Type: Journal article

Publication year: 2026

Journal

IEEETransactions on Automatic Control Institute of Electrical and Electronics Engineers (IEEE)

DOI: 10.1109/TAC.2026.3701274

Abstract

State-tree structures (STS) are data structures utilized in supervisory control theory to manage complexity and facilitate the design and analysis of large and intricate systems. The hierarchical architecture of an STS distinguishes itself by providing an efficient paradigm to synthesizing a monolithic supervisor, in contrast to discrete-event systems with unstructured state spaces. This study introduces an innovative methodology for decomposing an STS into a collection of parallel cascaded subsystems, where an inner supervisory control loop operates under the guidance of an outer loop. This decomposition allows for the synthesis of an optimal nonblocking supervisor without needing to track the global dynamics of the STS. Notably, this approach reduces computational complexity from exponential to additive costs by leveraging the binary decision diagram nodes used for the symbolic encoding of STS subsystems.

Authors with CRIS profile

Thomas Moor Professur für Regelungstechnik

Involved external institutions

Xidian University

China (CN)

How to cite

APA:

Wang, X., Li, Z., & Moor, T. (2026). Parallel Cascade Decomposition for Supervisory Control of State-Tree Structures. IEEETransactions on Automatic Control. https://doi.org/10.1109/TAC.2026.3701274

MLA:

Wang, Xi, Zhiwu Li, and Thomas Moor. "Parallel Cascade Decomposition for Supervisory Control of State-Tree Structures." IEEETransactions on Automatic Control (2026).

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