TY - JOUR
T1 - Output Feedback Control of Fuzzy Systems via Reduced-Order Approximation Technique
AU - Su, Xiaojie
AU - Chen, Qianqian
AU - Sun, Shaoxin
AU - Bing, Zhenshan
AU - Knoll, Alois
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2023/9/1
Y1 - 2023/9/1
N2 - This article focuses on the problem of designing the reduced-order dynamic output feedback (DOF) controller for discrete-time T-S fuzzy plants. Differing from the existing methodologies, the reduced-order approximation technique is applied to simplify the pregiven high-order DOF controller. The key point is to construct a reduced-order closed-loop model to approximate the original high-order closed-loop system. First, a new error auxiliary system between the high-order closed-loop system and the reduced-order closed-loop model is obtained. The sufficient conditions to guarantee that the corresponding error system is asymptotically stable with a prescribed H∞ performance index are developed. Then, the parameters of the desired reduced-order controller are derived by utilizing the projection lemma and the cone complementary linearization algorithm. Finally, the advantages of the proposed technique are illustrated by a series of simulation analysis.
AB - This article focuses on the problem of designing the reduced-order dynamic output feedback (DOF) controller for discrete-time T-S fuzzy plants. Differing from the existing methodologies, the reduced-order approximation technique is applied to simplify the pregiven high-order DOF controller. The key point is to construct a reduced-order closed-loop model to approximate the original high-order closed-loop system. First, a new error auxiliary system between the high-order closed-loop system and the reduced-order closed-loop model is obtained. The sufficient conditions to guarantee that the corresponding error system is asymptotically stable with a prescribed H∞ performance index are developed. Then, the parameters of the desired reduced-order controller are derived by utilizing the projection lemma and the cone complementary linearization algorithm. Finally, the advantages of the proposed technique are illustrated by a series of simulation analysis.
KW - Controller reduction
KW - fuzzy control
KW - fuzzy18 systems
KW - output feedback control
UR - http://www.scopus.com/inward/record.url?scp=85159830637&partnerID=8YFLogxK
U2 - 10.1109/TSMC.2023.3270289
DO - 10.1109/TSMC.2023.3270289
M3 - Article
AN - SCOPUS:85159830637
SN - 2168-2216
VL - 53
SP - 5466
EP - 5477
JO - IEEE Transactions on Systems, Man, and Cybernetics: Systems
JF - IEEE Transactions on Systems, Man, and Cybernetics: Systems
IS - 9
ER -