The Takagi-Sugeno (T-S) fuzzy multiple-variable integral control system with fuzzy state observer is designed for the coordinated control of multi-input-multi-output (MIMO) nonlinear boilerturbine system whose operating points vary within a wide range. Linear models are first derived from the original nonlinear model on several operating points. Next the fuzzy multi-variable integral controller...

Systems containing uncertainty are traditionally analyzed with probabilistic methods. However, for non-linear, non-Gaussian systems solutions can sometimes be very di4cult to obtain. The focus of this work is to determine if in such cases fuzzy dynamic system models may provide an alternative approach that more easily leads us to a good solution. In this paper, we present a fuzzy estimator whos...

In this paper variation of constants formula for the inhomogeneous fuzzy matrix difference system X(n + 1) = A(n)X(n) + F (n) is constructed by considering corresponding matrix difference inclusion Xβ(n+ 1) ∈ AβXβ(n) +Fβ(n), xβ(0) ∈ X0 β after presenting a procedure for solving the fuzzy difference equation by an example. Mathematics Subject Classification: 26E50, 34A12, 34A30

In this paper, we propose a new dynamical fuzzy modeling technique for SISO complex systems. It is seen that, the whole state-space of a complex system is divided into subspaces and a linear time-invariant (LTI) model is then used tu approximate the complex system in each subspace. However, the global dynamical fuzzy model of the complex system is derived by aggregating all subsystem poles and ...

A new approach is proposed for the pole placement of non-linear systems using the state feedback and fuzzy system. We use a new online fuzzy training method in order to identify and obtain a fuzzy model for an unknown non-linear system using only the system input and output. Then we linearize this identified model at each sampling time to have an approximate linear time-varying system. In order...

Different methods have been proposed for finding the non-negative solution of fully fuzzy linear system (FFLS) i.e. fuzzy linear system with fuzzy coefficients involving fuzzy variables. To the best of our knowledge, there is no method in the literature for finding the non-negative solution of a FFLS without any restriction on the coefficient matrix. In this paper a new computational method is ...

Abstract— The dynamic behavior of power systems is affected by the interactions between linear and nonlinear components. To analyze those complicated power systems, the linear approaches have been widely used so far. Especially, a synchronous generator has been designed by using linear models and traditional techniques. However, due to its wide operating range, complex dynamics, transient perfo...

This paper studies the H control problem for a nonlinear large-scale system with unknown disturbance. In the large-scale system, each subsystem “without” nonlinear interconnections and disturbance is transformed into a T-S fuzzy system. Moreover, based on a linear decomposition, the nonlinear interconnection corresponding to each subsystem is decomposed to a linear weighting interconnection wh...

The main aim of this paper intends to discuss the solution of general dual fuzzy linear system (GDFLS) C BX F AX + = + where A , B are real n m× matrix , F and C are fuzzy vectors, and the unknown vector X is a vector consisting of n fuzzy numbers, by a special algorithm based on a class of ABS algorithms called Huang algorithm. In special case, we apply the proposed algorithm for the solution ...