TY - JOUR
T1 - Performance Improvement via Iterative Connection of Passive Systems
AU - Urata, Kengo
AU - Inoue, Masaki
AU - Ishizaki, Takayuki
AU - Imura, Jun Ichi
N1 - Funding Information:
Manuscript received April 25, 2019; accepted July 6, 2019. Date of publication July 24, 2019; date of current version February 27, 2020. This work was supported in part by the JST-Mirai under Program 18077648, in part by JSPS Grant-in-Aid for Young Scientists (B) under Grant 17K14704, and in part by the JSPS Grand-in-Aid for Research Fellow under Grant 17J05742. Recommended by Associate Editor Y. Le Gorrec. (Corresponding author: Kengo Urata.) K. Urata, T. Ishizaki, and J. Imura are with the Graduate School of Engineering, Tokyo Institute of Technology, Tokyo 2-12-1, Japan (e-mail:, urata@cyb.sc.e.titech.ac.jp; ishizaki@cyb.sc.e.titech.ac.jp; imura@cyb. sc.e.titech.ac.jp).
PY - 2020/3
Y1 - 2020/3
N2 - This paper addresses model-set-based quantitative analysis of feedback systems. In particular, we find a model set describing the subsystems such that the performance improvement of the feedback system is achieved. To this end, we introduce the parameter-integrated passivity to accurately describe each passive subsystem and their feedback system. A model set describing passive systems is characterized by the two matrix parameters. The matrix parameters enable to evaluate the L_2-gain 'of the model set', which is defined as the L_2-gain of the worst-case system in the model set. With the parameter-integrated passivity, the quantitative analysis of a feedback system composed of two passive subsystems is provided as the parameter transition. Then, we find conditions on the matrix parameters to achieve the performance improvement such that the L_2-gain of the model set describing the feedback system is strictly less than that describing the subsystems. Subsequently, the performance improvement of the feedback system is extended to that of an iterative feedback system, which is a network system constructed by the feedback connection of multiple subsystems in a step-by-step manner. Then, we find conditions on the passivity parameters describing the baseline subsystem to achieve a gradual performance improvement with the subsystem connection.
AB - This paper addresses model-set-based quantitative analysis of feedback systems. In particular, we find a model set describing the subsystems such that the performance improvement of the feedback system is achieved. To this end, we introduce the parameter-integrated passivity to accurately describe each passive subsystem and their feedback system. A model set describing passive systems is characterized by the two matrix parameters. The matrix parameters enable to evaluate the L_2-gain 'of the model set', which is defined as the L_2-gain of the worst-case system in the model set. With the parameter-integrated passivity, the quantitative analysis of a feedback system composed of two passive subsystems is provided as the parameter transition. Then, we find conditions on the matrix parameters to achieve the performance improvement such that the L_2-gain of the model set describing the feedback system is strictly less than that describing the subsystems. Subsequently, the performance improvement of the feedback system is extended to that of an iterative feedback system, which is a network system constructed by the feedback connection of multiple subsystems in a step-by-step manner. Then, we find conditions on the passivity parameters describing the baseline subsystem to achieve a gradual performance improvement with the subsystem connection.
KW - Dissipativity
KW - gain
KW - model-set-based analysis
KW - passivity
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U2 - 10.1109/TAC.2019.2930806
DO - 10.1109/TAC.2019.2930806
M3 - Article
AN - SCOPUS:85081562286
VL - 65
SP - 1325
EP - 1332
JO - IEEE Transactions on Automatic Control
JF - IEEE Transactions on Automatic Control
SN - 0018-9286
IS - 3
M1 - 8771250
ER -