Nonlinear Simulation for Uncertain Systems Using Fuzzy Associative Memories

In this paper a fuzzy associative memory (FAM) is used as suitable representation of two-mass-spring system as a complex case study which is under structural uncertainties. For this purpose, a fuzzy rule-based system consists of a set of input data observed going into the system, a set of output data coming from the system and a set of rules that represents the behavior of the system. In general a set of fuzzy IF-THEN rules would be constructed according to input-output pairs. Therefore the most important task is to design a FAM as a fuzzy system that characterizes the input-output behavior represented by the input-output pairs. There are much research efforts in the literature using Monte Carlo simulation (MCS) which is a direct and simple numerical method, however, it can be computationally very expensive and time consuming as the governingdynamic equations of the system to be simulated for each random sample using the MCS. In this paper, fuzzy associative memory (FAM) also are obtained to simply calculate the probability of failure in the MCS, instead of direct solution of dynamic equation of system.

کلیدواژه ها:

fuzzy rule ، fuzzy system ، modeling and simulation ، uncertainty