Application of fuzzy logic in resistive fault modeling and simulation

Abstract

Abstract-Real defects (e.g., resistive stuck at or bridging faults) in the very large-scale integration (VLSI) circuits cause intermediate voltages which cannot be modeled as ideal shorts. In this paper, we first show that the traditional zero-resistance model is not sufficient for fault simulation. Then, we present a resistive fault model for real defects and use fuzzy logic techniques for fault simulation and test pattern generation at the gate level. Our method uses Takagi-Sugeno (TS) fuzzy system to accurately model digital VLSI circuits and produces much more realistic fault coverage compared to the conventional methods. The experimental results include the fault coverage and test-pattern statistics for the ISCAS85 benchmarks.Index Terms-Bridging faults, fault simulation, fuzzy logic, Mamdani model, resistive faults, stuck at faults, Takagi-Sugeno (TS) model, test-pattern generation.

Intelligent Modeling and Control of Washing Machine Using Locally Linear Neuro‐fuzzy (Llnf) Modeling and Modified Brain Emotional Learning Based Intelligent Controller (Belbic)

“…In addition, an appropriate fuzzy logic controller can overcome the environmental variation during operation processes [1]. Due to these characteristics, many plants and processes use fuzzy logic control [2][3][4][5][6][7]. Several attempts have been made to model the emotional behavior of human brain [8][9][10].…”