There are two approaches to extract a linear model from a Takagi-Sugeno fuzzy model for model based control. The first local approach obtains the linear model by interpolating the parameters of the local models in the TS model, while the second one is based on linearization by Taylor expansion. The locally interpreted interpolated model is not identical to the model obtained by the linearizatio...

In this paper, a new method of predictive control is presented. In this approach, a well-known method of predictive functional control is combined with fuzzy model of the process. The prediction is based on fuzzy model given in the form of Takagi–Sugeno (T–S) type. The proposed fuzzy predictive control has been evaluated by implementation on heat-exchanger plant, which exhibits a strong nonline...

-This study addresses a fuzzy Lyapunov method for the stability analysis of time-delay fuzzy systems subject to external disturbances. The Takagi-Sugeno (T-S) fuzzy model and parallel distributed compensation (PDC) scheme are first employed to design a nonlinear fuzzy controller in order to stabilize the time-delay fuzzy systems. According to the controlled system, the H infinity criterion is d...

This paper proposes an identification scheme for a complex liquid effluent incinerator process. This scheme is developed to obtain a MIMO (Multiple Input Single Output) TS (Takagi-Sugeno) fuzzy model where the modified Gath Geva clustering algorithm is used to determine the antecedent part as the consequent parameters are estimated by RLS (Recursive Least Square) algorithm.

This paper describes optimization of the Takagi-Sugeno fuzzy model. To prove the existence of optimal control, we apply compactness of a set of membership functions in L space and continuity of approximate reasoning and show the existence of a pair of membership functions which minimize the quadratic performance function.

This paper presents the nano-positioning control of a piezoelectric platform. A Bouc-Wen model is established to describe the nonlinear hysteretic effect of piezoelectric systems. Three kinds of compensators, traditional PI controller, PI-like fuzzy logic controller (FLC) and adaptive PI-FLC controller, are designed for the piezoelectric systems. The adaptive PI controller is tuned on-line by m...

In recent years, the Takagi–Sugeno (T–S) fuzzy model has been commonly used for the approximation of nonlinear systems. Using the T-S fuzzy model, nonlinear systems can be converted into linear time-varying systems, which can reduce approximation errors compared with the conventional Taylor approximation. In this paper, we propose a new nonlinear filter with a finite impulse response (FIR) stru...

An iterative backward selection method for determination of relevant input variables in data-driven fuzzy modeling is presented. The method utilizes parameters of the Takagi-Sugeno model as a factor to determine the significance of input variables. As a result, it is less computationally intensive than most of the existing methods for input variable selection.