System of linear equations is a problem that may be solved for solving many problems in various areas of applied sciences. Fuzzy methods constitute an important mathematical and computational tool for modeling real-world systems with uncertainties of parameters. The paper discusses fully fuzzy linear systems (shown as FFLS) using embedding approach to find its non-zero fuzzy number solutions. W...

kim and bishu (fuzzy sets and systems 100 (1998) 343-352) proposeda modification of fuzzy linear regression analysis. their modificationis based on a criterion of minimizing the difference of the fuzzy membershipvalues between the observed and estimated fuzzy numbers. we show that theirmethod often does not find acceptable fuzzy linear regression coefficients andto overcome this shortcoming, pr...

This paper investigates the application of fuzzy model and generalised predictive control strategy for the construction of a model-based predictive fuzzy controller for non-linear processes. In this method a GPC controller is used with the Takagi Sugeno Kang (TSK) piece-wise fuzzy modeling approach in an adaptive strategy. The developed method is applied to control a continuous stirred tank rea...

This paper describes a new methodology for the systematic design of fuzzy PID controllers based on theoretical fuzzy analysis and genetic-based optimization. An important feature of the proposed controller is its simple structure. It uses a one-input fuzzy inference with three rules and at most six tuning parameters. A closed-form solution for the control action is defined in terms of the nonli...

In this paper, the main is to develop a method to solve an arbitrary inconsistent fuzzy linear system by using the embedding approach. Considering the existing of minimal solution to m × n linear fuzzy system is done. To illustrate the proposed model numerical examples are given and obtained results are discussed.

This paper proposes inverse fuzzy-model-based feed-forward fuzzy controllers to compensate non-linear terms that affect the system dynamics. The gradient-descent algorithm can be used on-line to form adaptive fuzzy controllers. This ability allows these controllers to be used in applications were the knowledge to control the process does not exist or the process is subject to changes in its dyn...

In this paper, we introduce and study a mixed variational inclusion problem involving infinite family of fuzzy mappings. An iterative algorithm is constructed for solving a mixed variational inclusion problem involving infinite family of fuzzy mappings and the convergence of iterative sequences generated by the proposed algorithm is proved. Some illustrative examples are also given.

The paper introduces an exclusion/inclusion fuzzy classification neural network. The network is based on our GFMM [3] and it allows for two distinct types of hyperboxes to be created: inclusion hyperboxes that correspond directly to those considered in GFMM, and exclusion hyperboxes that represent contentious areas of the pattern space. The subtraction of the exclusion hyperboxes from the inclu...