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Robust Double‐integral T‐S Fuzzy Output Regulation for Nonlinear Systems
Author(s) -
Lian KuangYow,
Liu ChienHung,
Chiu ChianSong
Publication year - 2018
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.1652
Subject(s) - control theory (sociology) , integrator , mathematics , fuzzy logic , robustness (evolution) , parametric statistics , nonlinear system , fuzzy control system , robust control , affine transformation , computer science , control (management) , artificial intelligence , quantum mechanics , computer network , biochemistry , chemistry , statistics , physics , bandwidth (computing) , pure mathematics , gene
Abstract This paper proposes a robust double‐integral T‐S fuzzy output regulator design for affine nonlinear systems in the presence of parametric uncertainty and external disturbance. First, we adopt double integrators (an error integrator and an input integrator) to obtain an augmented T‐S fuzzy model representation which has a common input matrix of fuzzy rules. This property yields less stability conditions. Next, by introducing a set of virtual desired variables (VDVs), a double‐integral VDV‐based fuzzy regulator is proposed to cope with unknown bias and to achieve asymptotical output regulation. Afterward, the controller is simplified to avoid VDV calculation and enhance robustness to uncertainty and external disturbance. In contrast to traditional regulation design, the double‐integral non‐VDV fuzzy regulator design reduces the number of fuzzy controller rules and stability LMIs. Moreover, the error coordinate transformation is removed and the uncertainty is allowed in this paper. Finally, a DC/DC buck converter system is taken as the example to demonstrate the expected performance.