Membership-Function-Dependent Control Design of Interval Type-2 Sampled-Data Fuzzy-Model-Based Output-Feedback Tracking Control System

被引:18
作者
Chen, Ming [1 ]
Lam, Hak-Keung [1 ]
Xiao, Bo [2 ,3 ]
Zhou, Hongying [1 ]
机构
[1] Kings Coll London, Dept Engn, London WC2R 2LS, England
[2] Imperial Coll London, Hamlyn Ctr Robot Surg, London SW7 2AZ, England
[3] Imperial Coll London, Dept Comp, London SW7 2AZ, England
关键词
Imperfect premise matching (IPM); interval type-2 (IT2) Takagi-Sugeno (T-S) fuzzy model; membership-function-dependent (MFD) stability analysis approach; output-feedback (OF) tracking control; sampled-data (SD) type; two-sided looped-functional-based approach; STABILITY ANALYSIS; ROBUST STABILITY; LINEAR-SYSTEMS; STABILIZATION; SUBJECT; LOGIC;
D O I
10.1109/TFUZZ.2021.3130303
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This article focuses on the stability analysis and control design of an interval type-2 sampled-data fuzzy-model-based output-feedback (IT2SDFMBOF) tracking control system, which is formed by the interval type-2 (IT2) Takagi-Sugeno (T-S) fuzzy model, the stable reference model, and the interval type-2 sampled-data output-feedback (IT2SDOF) fuzzy controller. The design goal is to establish a proper IT2SDOF fuzzy controller that is able to drive the states of the nonlinear plant subject to uncertainties to track those of the stable reference model, and the H-infinity performance index is adopted to optimize the tracking control performance. To improve the robustness of the IT2SDOF fuzzy controller against uncertainties of the nonlinear plant, IT2 fuzzy sets are utilized. Considering that the tracking control system is sampled-data (SD) type, a two-sided looped-functional-based approach exploiting the information on the interval from time t(k) to t and the interval from time t to t(k+1) is applied to enhance the stability analysis. The imperfect premise matching (IPM) concept permits the number of rules and the premise membership functions of the IT2 T-S fuzzy model and the IT2SDOF fuzzy controller to be different, which can be employed to promote the design flexibility. The tracking control system with the SD type and IPM design will cause the membership grades between the IT2 T-S fuzzy model and the IT2SDOF fuzzy controller to be mismatched. In addition, the membership-function-dependent stability analysis approach that can introduce the boundary information of membership functions into the stability analysis is used to relax the stability conditions. The relaxed stability conditions subject to the H-infinity performance building on the Lyapunov stability theory are developed in terms of linear matrix inequalities. Simulation results demonstrate the effectiveness of the proposed IT2SDFMBOF tracking control system.
引用
收藏
页码:3823 / 3832
页数:10
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