The problem of robust fuzzy control for a class of nonlinear fuzzy impulsive singular perturbed systems with time-varying delay is investigated by employing Lyapunov functions. The nonlinear delay system is built based on the well-known T–S fuzzy model. The so-called parallel distributed compensation idea is employed to design the state feedback controller. Sufficient conditions for global expo...

In this paper we consider the control problem of Dynamic Positioning Systems for Ships (DPSS). It interests as a case which study in nonlinear controller design because the model exhibits nonlinear interaction in three degrees of freedom (surge, sway, and yaw) by means of main propellers aft of the ship. The DPSS system considered in this paper is modeled by a Takagi-Sugeno (T-S) type fuzzy mod...

To improve the problem that the parameter identification for fuzzy neural network has many time complexities in calculating, an improved T-S fuzzy inference method and an parameter identification method for fuzzy neural network are proposed. It mainly includes three parts. First, improved fuzzy inference method based on production term for T-S Fuzzy model is explained. Then, compared with exist...

This paper presents a switch methodology together with a sum of squares (SOS) techniques to synthesize a nonlinear controller for a polynomial Takagi-Sugeno (TS) fuzzy model. A polynomial T-S fuzzy model adopts a polynomial representation of the nonlinear dynamics in its consequent part, which make it less susceptible to linearization errors. With respect to polynomial T-S fuzzy models, a fuzzy...

In this work, three topics which are important for the further development of fuzzy systems are chosen to be investigated. First, the mathematical aspects of fuzzy relational equations (FREs) are explored. Solving FREs is one of the most important problems in fuzzy systems. In order to identify the algebraic information of the fuzzy space, two new tools, called fuzzy multiplicative inversion an...

• TOP OF ARTICLE • INPUT-OUTPUT SYSTEM REPRESENTATION • NONLINEAR DIFFERENTIAL ALGEBRAIC REPRESENTATION • VOLTERRA REPRESENTATION • STATE-SPACE REPRESENTATION • BILINEAR REPRESENTATION • NARMA REPRESENTATION • FUZZY-LOGIC NONLINEAR REPRESENTATION • NONLINEAR REPRESENTATION USING NEURAL NETWORKS • MODEL-FREE REPRESENTATION • FEATURES OF NONLINEAR REPRESENTATIONS • EXAMPLE • CONCLUDING REMARKS • ...

Pitch control is one of t he  major aspects of wind turbine control, particularly over high wi nd s p e e d  a n d  oscillations. General El e c t r i c  (GE) model of  wi n d  t ur bi ne  i s practically compatible with the structure of the wind turbines. I t  h a s  b e e n  p r o v e d t h a t  simulation results using this model are closer to the actual case, compared to other available mod...

Aiming at the characteristics which variable air volume air conditioning system is multi-variable, nonlinear and uncertain system, normal fuzzy neural network is hard to meet the requirements which dynamic control of multi-variable. In this paper, we put forward a recursive neural network predictive control strategy based on T-S fuzzy model. Through T-S fuzzy recursive neural network predictor ...

A new and efficient approach is presented that lead to improve the local and global approximation (matching) and modelling capability of Takagi-Sugeno (T-S) fuzzy model. The main aim is obtaining high function approximation accuracy and fast convergence. The main problem encountered is that T-S model can not be applied when the membership functions are overlapped by pairs. This restricts the ap...