In recent years, it has become increasingly important to incorporate explicit dynamics in economic analysis. These two tools that mathematicians have developed, differential equations and optimal control theory, are probably the most basic for economists to analyze dynamic problems. In this paper I will consider the linear differential equations on the plane (phase diagram) and elements of nonl...

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...

the fuzzy linear regression model with fuzzy input-output data andcrisp coefficients is studied in this paper. a linear programmingmodel based on goal programming is proposed to calculate theregression coefficients. in contrast with most of the previous works, theproposed model takes into account the centers of fuzzy data as animportant feature as well as their spreads in the procedure ofconstr...

in this paper, a new method is proposed to find the fuzzy optimal solution of fully fuzzy linear programming (abbreviated to fflp) problems. also, we employ linear programming (lp) with equality constraints to find a nonegative fuzzy number vector x which satisfies ax =b, where a is a fuzzy number matrix. then we investigate the existence of a positive solution of fully fuzzy linear system (ffls).

The dynamic equations of motion for a mechanical manipulator are highly non-linear and complex. It is therefore, very difficult to implement real-time control based on a detailed dynamic model of a robot, if not impossible (Luh et al., 1980; Lee et al., 1982). The control problem becomes more difficult if adaptive control is necessary to accommodate changing operational conditions. Such a requi...

Abstract: This paper focuses on the Fuzzy Frequency Response: Definition and Analysis for Uncertain Dynamic Systems. In terms of transfer function, the uncertain dynamic system is partitioned into several linear sub-models and it is organized into Takagi-Sugeno (TS) fuzzy structure. The main contribution of this approach is demonstrated, from a Theorem, that fuzzy frequency response is a bounda...

Controller design strategy for Takagi-Sugeno (T-S) fuzzy systems is considered in the two-degree-of-freedom (TDOF) framework. Firstly, coprime factorization described in the state space formulas for T-S fuzzy systems is introduced based on a common Lyapunov function. Secondly, based on this coprime factorization, TDOF framework for LTI systems is extended to be applied to T-S fuzzy systems. Con...

in this paper, a numerical method for nding minimal solution of a mn fullyfuzzy linear system of the form ax = b based on pseudo inverse calculation,is given when the central matrix of coecients is row full rank or column fullrank, and where a~ is a non-negative fuzzy mn matrix, the unknown vectorx is a vector consisting of n non-negative fuzzy numbers and the constant b isa vector consisti...

controlling a system with minimum information and regardless of dynamic equations which dominate systems is the aim of intelligent control. one of the common approaches for process control is applying shewhart's quality control charts. neuro-fuzzy networks, as one of the branches of artificial intelligence (ai), can play an effective role in the enforcement of process control's common...

In this paper a genetic algorithms approach for solving the linear and quadratic fuzzy equations B x A ~ ~ ~ = and C x B x A ~ ~ ~ ~ ~ 2 = + , where A~ , B~ , C~ and x ~ are fuzzy numbers is proposed by genetic algorithms. Our genetic based method initially starts with a set of random fuzzy solutions. Then in each generation of genetic algorithms, the solution candidates converge more to better...