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Volume 11 Issue 3
Mar.  2024

IEEE/CAA Journal of Automatica Sinica

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Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2024  >  11(3): 698-707
N. Wang, X. Liang, H. Li, and X. Lu, “Decentralized optimal control and stabilization of interconnected systems with asymmetric information,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 3, pp. 698–707, Mar. 2024. doi: 10.1109/JAS.2023.124044
Citation: N. Wang, X. Liang, H. Li, and X. Lu, “Decentralized optimal control and stabilization of interconnected systems with asymmetric information,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 3, pp. 698–707, Mar. 2024. doi: 10.1109/JAS.2023.124044
shu

Decentralized Optimal Control and Stabilization of Interconnected Systems With Asymmetric Information

doi: 10.1109/JAS.2023.124044
Funds:  This work was supported by the National Natural Science Foundation of China (62273213, 62073199, 62103241), Natural Science Foundation of Shandong Province for Innovation and Development Joint Funds (ZR2022LZH001), Natural Science Foundation of Shandong Province (ZR2020MF095, ZR2021QF107), Taishan Scholarship Construction Engineering, the Original Exploratory Program Project of National Natural Science Foundation of China (62250056), Major Basic Research of Natural Science Foundation of Shandong Province (ZR2021ZD14) and High-level Talent Team Project of Qingdao West Coast New Area (RCTD-JC-2019-05)
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    Abstract
  • The paper addresses the decentralized optimal control and stabilization problems for interconnected systems subject to asymmetric information. Compared with previous work, a closed-loop optimal solution to the control problem and sufficient and necessary conditions for the stabilization problem of the interconnected systems are given for the first time. The main challenge lies in three aspects: Firstly, the asymmetric information results in coupling between control and estimation and failure of the separation principle. Secondly, two extra unknown variables are generated by asymmetric information (different information filtration) when solving forward-backward stochastic difference equations. Thirdly, the existence of additive noise makes the study of mean-square boundedness an obstacle. The adopted technique is proving and assuming the linear form of controllers and establishing the equivalence between the two systems with and without additive noise. A dual-motor parallel drive system is presented to demonstrate the validity of the proposed algorithm.

     

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