Inspired by the phenomenon of symbiosis in natural ecosystems a multi-swarm cooperative particle swarm optimizer (MCPSO) is proposed as a new fuzzy modeling strategy for identification and control of non-linear dynamical systems. In MCPSO, the population consists of one master swarm and several slave swarms. The slave swarms execute particle swarm optimization (PSO) or its variants independentl...

We describe in this paper a new method for automated simulation of non-linear dynamical systems. This method is based on a hybrid fuzzy-fractal-genetic approach to achieve, in an efficient way, automated simulation of a particular dynamical system given its mathematical model. The use of genetic algorithms is to achieve automated parameter selection for the mathematical models. The use of fuzzy...

Fuzzy differential equations are used in modeling problems in science and engineering. For instance, it is known that the knowledge of dynamical systems modeled by ordinary differential equations is often incomplete or vague. While, fuzzy differential equations represent a proper way to model dynamical systems under uncertainty and vagueness. In this paper, two methods for solving first order l...

Let X be a compact metric space and continuous map f:X→X which defines discrete dynamical system (X,f). The f induces two natural maps, namely f¯:K(X)→K(X) on the hyperspace K(X) of non-empty subspaces Zadeh’s extension f^:F(X)→F(X) F(X) normal fuzzy set. In this work, we analyze interaction some orbit tracing properties, specification shadowing properties (X,f) its induced systems (K(X),f¯) (F...

In order to more effectively cope with the real world problems of vagueness, imprecise and subjectivity, fuzzy event systems were proposed recently. In this paper, we investigate the controllability and the observability property of two systems that one of them has fuzzy variables and the other one has fuzzy coefficients and fuzzy variables (fully fuzzy system). Also, sufficient conditions for ...