The Takagi-Sugeno fuzzy model is described by fuzzy if-then rules which represent local linear systems of the underlining nonlinear systems (Takagi & Sugeno, 1985; Tanaka et al., 1996; Tanaka & Sugeno, 1992) and thus it can describe a wide class of nonlinear systems. In the last decade, nonlinear control design methods based on Takagi-Sugeno fuzzy system have been explored. Since the stability ...

It has been shown that the problem of equivalent and minimization of fuzzy Mealy machines can be resolved via their algebraic study. However, no attention has paid to study fuzzy Mealy machines topologically. This paper introduces topology on the state set of a fuzzy Mealy machine and study of various kinds of fuzzy Mealy machines viz. cyclic, retrievable, strongly connected, with exchange prop...

Fuzzy measures are monotonic set functions used for modelling strength of coalition of criteria in multicriteria decision-making. However, the practical application of fuzzy measures is difficult. The problem of fuzzy measures acquisition can be thought as an engineering problem. In our study, we have investigated the issue of fuzzy measures acquisition from an engineering perspective. Many met...

For discrete-time Takagi–Sugeno (TS) fuzzy systems, we propose an state-feedback fuzzy controller associated with a fuzzy weighting-dependent Lyapunov function. The controller, which is designed via parameterized linear matrix inequalities (PLMIs), employs not only the current-time but also the one-step-past information on the time-varying fuzzy weighting functions. Appropriately selecting the ...

Based on fuzzy language field and fuzzy language value structure, a new knowledge representation frame is presented. A generalized cell automation and the corresponding generalized induction logic causal model are also proposed, which can synthetically process random and fuzzy indeterminacy. Thus, a new indeterminacy causal induction auto-reasoning mechanism is presented on the basis of fuzzy s...

In this paper, first a new algorithm for pole assignment of closed-loop multi-variable controllable systems in a prescribed region of the z-plane is presented. Then, robust state feedback controllers are designed by implementing a neural fuzzy system for the placement of closed-loop poles of a controllable system in a prescribed region in the left-hand side of z-plane. A new method based on the...

Abstract: In this paper hybrid fuzzy model based predictive control (HFMBPC) is addressed, proposed and tested. The proposed hybrid fuzzy convolution model consists of a steady-state fuzzy model and a gain independent impulse response model. The proposed model is tested in model based predictive control of the concentration control in the chemical reactor, manipulating its flow rate. The paper ...

Reliability analysis is one of the important constituent parts of elevator safety evaluation. In order to obtain the exact value of fault probability of components in elevator system, by combining fuzzy theory with Bayesian network approach, we proposed a reliability analysis method of multi-state system based on fuzzy Bayesian networks. By expanding the traditional two-state Bayesian network t...