Robust \(H_{\infty}\) control of multiple time-delay uncertain nonlinear system using fuzzy model and adaptive neural network
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Publication:1885712
DOI10.1016/j.fss.2003.09.009zbMath1053.93023OpenAlexW2079584267MaRDI QIDQ1885712
Publication date: 12 November 2004
Published in: Fuzzy Sets and Systems (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.fss.2003.09.009
stabilityNeural networkchaotic systemuncertain nonlinear systemsFuzzy T-S modelFuzzy-model-based controlMultiple time-delay
Fuzzy control/observation systems (93C42) Nonlinear systems in control theory (93C10) Adaptive control/observation systems (93C40) (H^infty)-control (93B36)
Related Items (6)
Neural-network-based optimal fuzzy controller design for nonlinear systems ⋮ Robust digital design of continuous-time nonlinear control systems using adaptive prediction and random-local-optimal NARMAX model ⋮ New delay-dependent stabilization conditions of T-S fuzzy systems with constant delay ⋮ Guaranteed cost control of T-S fuzzy systems with state and input delays ⋮ Observer-based fuzzy control design with adaptation to delay parameter for time-delay systems ⋮ Fuzzy hyperbolic neural network with time-varying delays
Cites Work
- Quadratic stability analysis of the Takagi-Sugeno fuzzy model
- Analysis and design of fuzzy control system
- Practical design of nonlinear fuzzy controllers with stability analysis for regulating processes with unknown mathematical models
- Stability analysis and synthesis of nonlinear time-delay systems via linear Takagi-Sugeno fuzzy models
- Dynamic parallel distributed compensation for Takagi-Sugeno fuzzy systems: An LMI approach
- Fuzzy identification of systems and its applications to modeling and control
- Control laws for Takagi-Sugeno fuzzy models
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