Discrete fuzzy control of time-delay affine Takagi–Sugeno fuzzy models with H∞ constraint

Chang, Wen‐Jer

doi:10.1049/ip-cta:20050306

Cited by 31 publications

(49 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…According to Theorem 2, an ILMI algorithm is developed to find the feasible solutions for the stability conditions (26)(27). The purpose of this algorithm is to iteratively search for P, S, P d , F i , ijq , ξ α and to update the auxiliary constant matrix R until 1. α <…”

Section: Fuzzy Controller Design For Dptda T-s Fuzzy Models Via Ilmi mentioning

confidence: 99%

“…The BMI conditions can not be easily solved via a convex optimization algorithm. For this reason, an ILMI algorithm [24,26,27] has been presented to solve the BMI problem. In this paper, a modified ILMI algorithm is developed to find feasible solutions for the synthesis problem of fuzzy controller design for the DPTDA T-S fuzzy models.…”

Section: Introductionmentioning

confidence: 99%

“…Generally, the T-S fuzzy models can be separated into the homogeneous fuzzy models [13][14][15][16][17][18][19][20][21][22][23] and the affine fuzzy models [24][25][26][27]. The homogeneous one can be referred to the T-S fuzzy model of which consequent part is linear without constant bias term.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Robust fuzzy control for discrete perturbed time-delay affine Takagi-Sugeno fuzzy models

Chang

Huang

2011

Int. J. Control Autom. Syst.

View full text Add to dashboard Cite

The purpose of this paper is to study the stability analysis and controller synthesis principles of Discrete Perturbed Time-Delay Affine (DPTDA) Takagi-Sugeno (T-S) fuzzy models. In general, the T-S fuzzy model is a weighted sum of some linear subsystems via fuzzy membership functions. This paper considers fuzzy rules include both linear nominal parts and uncertain parameters in the time-delay affine T-S fuzzy model. For DPTDA T-S fuzzy models, the T-S fuzzy control scheme is used to confront the H ∞ performance constraints. Some sufficient conditions are derived on robust H ∞ disturbance attenuation in which both robust stability and a prescribed performance are required to be achieved. In order to find suitable fuzzy controllers, the Iterative Linear Matrix Inequality (ILMI) algorithm is employed to solve these sufficient conditions. At last, a numerical simulation for the nonlinear truck-trailer system is given to show the applications of the present design approach.

show abstract

Section: Fuzzy Controller Design For Dptda T-s Fuzzy Models Via Ilmi mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Robust fuzzy control for discrete perturbed time-delay affine Takagi-Sugeno fuzzy models

Chang

Huang

2011

Int. J. Control Autom. Syst.

View full text Add to dashboard Cite

show abstract

“…Nounou and the coauthor propose three fuzzy model predictive control algorithms [21]. Chang and coauthors propose LMI-based fuzzy controllers for continuous and discrete affine T-S fuzzy systems with time-delay or constraint [3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Affine TS-model-based fuzzy regulating/servo control design

Wu¹

2007

Fuzzy Sets and Systems

View full text Add to dashboard Cite

“…Recently, some authors proposed several control methods to control the nonlinear systems by using fuzzy system models [1][2][3][4][5][6][7][8][9]. The affine fuzzy system means the fuzzy system of which consequent part is affined and which has a constant bias term.…”

Section: Introductionmentioning

confidence: 99%

Study of Inverted Pendulum Robot Using Fuzzy Servo Control Method

Wang

Zhang

et al. 2012

International Journal of Advanced Robotic Systems

View full text Add to dashboard Cite

The inverted pendulum robot is a classical problem in controls. The inherit instabilities in the setup make it a natural target for a control system. Inverted pendulum robot is suitable to use for investigation and verification of various control methods for dynamic systems. Maintaining an equilibrium position of the pendulum pointing up is a challenge as this equilibrium position is unstable. As the inverted pendulum robot system is nonlinear it is well-suited to be controlled by fuzzy logic. In this paper, Lagrange method has been applied to develop the mathematical model of the system. The objective of the simulation to be shown using the fuzzy control method can stabilize the nonlinear system of inverted pendulum robot.

show abstract

Discrete fuzzy control of time-delay affine Takagi–Sugeno fuzzy models with H∞ constraint

Cited by 31 publications

References 20 publications

Robust fuzzy control for discrete perturbed time-delay affine Takagi-Sugeno fuzzy models

Robust fuzzy control for discrete perturbed time-delay affine Takagi-Sugeno fuzzy models

Affine TS-model-based fuzzy regulating/servo control design

Study of Inverted Pendulum Robot Using Fuzzy Servo Control Method

Contact Info

Product

Resources

About