TY - JOUR
T1 - Subspace-Aided Distributed Monitoring and Control Performance Optimization Approach for Interconnected Industrial Systems
AU - Huo, Mingyi
AU - Luo, Hao
AU - Xiao, Bing
AU - Jiang, Yuchen
N1 - Publisher Copyright:
© 2025 IEEE. All rights reserved.
PY - 2025
Y1 - 2025
N2 - This article proposes a subspace-aided distributed monitoring and control performance optimization integrated framework and the corresponding distributed monitoring and optimization approaches equivalent to centralized designs. It effectively realizes the online global control performance optimization and solves the predesigned controller parameter adjustment limitation. The main contributions of this article are as follows. First, the proposed distributed monitoring and optimization modules can cooperate to establish a subspace-aided distributed integrated framework. The framework effectively addresses the issue of separate design in monitoring and optimization, achieving modularization that facilitates the expansion and maintenance of interconnected systems. Second, the proposed subspace-aided control performance optimization approach breaks the limitations of existing methods that require predesigned controller parameter adjustments, which can achieve distributed control performance optimization while ensuring closed-loop stability of interconnected systems. Third, the proposed optimization approach can automatically adjust the iterative step size, avoiding the disadvantage of manually setting the step size in the traditional optimization algorithm. It shortens the optimization time and reduces the design difficulty. The new methodologies have been evaluated against the current techniques and validated using an interconnected dc motor system, which holds significant engineering importance.
AB - This article proposes a subspace-aided distributed monitoring and control performance optimization integrated framework and the corresponding distributed monitoring and optimization approaches equivalent to centralized designs. It effectively realizes the online global control performance optimization and solves the predesigned controller parameter adjustment limitation. The main contributions of this article are as follows. First, the proposed distributed monitoring and optimization modules can cooperate to establish a subspace-aided distributed integrated framework. The framework effectively addresses the issue of separate design in monitoring and optimization, achieving modularization that facilitates the expansion and maintenance of interconnected systems. Second, the proposed subspace-aided control performance optimization approach breaks the limitations of existing methods that require predesigned controller parameter adjustments, which can achieve distributed control performance optimization while ensuring closed-loop stability of interconnected systems. Third, the proposed optimization approach can automatically adjust the iterative step size, avoiding the disadvantage of manually setting the step size in the traditional optimization algorithm. It shortens the optimization time and reduces the design difficulty. The new methodologies have been evaluated against the current techniques and validated using an interconnected dc motor system, which holds significant engineering importance.
KW - Distributed control performance optimization
KW - distributed integrated framework
KW - distributed monitoring
KW - subspace-aided
UR - http://www.scopus.com/inward/record.url?scp=85219712682&partnerID=8YFLogxK
U2 - 10.1109/TII.2025.3534416
DO - 10.1109/TII.2025.3534416
M3 - 文章
AN - SCOPUS:85219712682
SN - 1551-3203
JO - IEEE Transactions on Industrial Informatics
JF - IEEE Transactions on Industrial Informatics
ER -