Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach
Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach
Switching control of an R/C hovercraft: stabilization and smoothswitching
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
An improved stability criterion for T-S fuzzy discrete systems via vertex expression
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A Novel Stabilization Criterion for Large-Scale T–S Fuzzy Systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Finite-Dimensional Constrained Fuzzy Control for a Class of Nonlinear Distributed Process Systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A Survey on Analysis and Design of Model-Based Fuzzy Control Systems
IEEE Transactions on Fuzzy Systems
Sum-of-squares-based stability analysis of polynomial fuzzy-model-based control systems
FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
Polynomial fuzzy models for nonlinear control: a Taylor series approach
IEEE Transactions on Fuzzy Systems
SOS-based stability analysis of polynomial fuzzy control systems via polynomial membership functions
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
IEEE Transactions on Fuzzy Systems
Robust guaranteed cost control of uncertain fuzzy systems under time-varying sampling
Applied Soft Computing
IEEE Transactions on Fuzzy Systems
Passivity analysis and passive control of fuzzy systems with time-varying delays
Fuzzy Sets and Systems
Stability analysis of polynomial fuzzy models via polynomial fuzzy Lyapunov functions
Fuzzy Sets and Systems
WCCI'12 Proceedings of the 2012 World Congress conference on Advances in Computational Intelligence
H∞ state feedback controller design for continuous-time T-S fuzzy systems in finite frequency domain
Information Sciences: an International Journal
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This correspondence paper presents the guaranteed cost control of polynomial fuzzy systems via a sum of squares (SOS) approach. First, we present a polynomial fuzzy model and controller that are more general representations of the well-known Takagi-Sugeno (T-S) fuzzy model and controller, respectively. Second, we derive a guaranteed cost control design condition based on polynomial Lyapunov functions. Hence, the design approach discussed in this correspondence paper is more general than the existing LMI approaches (to T-S fuzzy control system designs) based on quadratic Lyapunov functions. The design condition realizes a guaranteed cost control by minimizing the upper bound of a given performance function. In addition, the design condition in the proposed approach can be represented in terms of SOS and is numerically (partially symbolically) solved via the recent developed SOSTOOLS. To illustrate the validity of the design approach, two design examples are provided. The first example deals with a complicated nonlinear system. The second example presents micro helicopter control. Both the examples show that our approach provides more extensive design results for the existing LMI approach.