DocumentCode :
3582212
Title :
Effective T-S fuzzy model for decentralized control
Author :
Qian-Fang Liao ; Wen-Jian Cai ; You-Yi Wang
Author_Institution :
Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore, Singapore
fYear :
2014
Firstpage :
1
Lastpage :
6
Abstract :
In order to facilitate decentralized fuzzy controller designs for multi-input-multi-output (MIMO) processes, this paper presents a novel manner, called effective Takagi-Sugeno (T-S) fuzzy model (ETSM), to describe the interactions among the loops. For a certain control-loop of an MIMO process, in terms of relative normalized gain array (RNGA) based loop pairing criterion, simple calculating procedure is given to obtain an ETSM based on its individual open-loop T-S fuzzy model. With the ETSMs of control-loops, an MIMO process can be approximately regarded as multiple non-interacting single loops such that each local controller of a decentralized control system can be independently designed using linear single-input-single-output (SISO) control algorithms. Compared with the existing decentralized fuzzy control methods adding extra terms to individual open-loop models to characterize interactions, ETSM is a practical and low-cost way. While compared with the existing effective transfer function (ETF) methods, ETSM is an extension that can proceed without requiring exact process mathematical functions, and lays a basis to develop robust controller since fuzzy system is strong in handling uncertainties. In case study, a nonlinear MIMO process is used as an example to demonstrate the effectiveness of the proposed ETSM method.
Keywords :
MIMO systems; control system synthesis; decentralised control; fuzzy control; linear systems; robust control; ETSM; MIMO process; RNGA based loop pairing criterion; SISO control algorithm; control loop; decentralized control system; decentralized fuzzy controller design; effective Takagi-Sugeno fuzzy model; linear single input single output control algorithm; multiple input multiple output; open loop T-S fuzzy model; relative normalized gain array; robust controller; uncertainty handling; Computational modeling; Decentralized control; MIMO; Mathematical model; Process control; Robustness; Uncertainty; Decentralized control; Effective model; Loop pairing; RNGA; T-S fuzzy model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information and Automation for Sustainability (ICIAfS), 2014 7th International Conference on
Type :
conf
DOI :
10.1109/ICIAFS.2014.7069538
Filename :
7069538
Link To Document :
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