RT info:eu-repo/semantics/article
T1 Application of a Fuzzy Inference System for Optimization of an Amplifier Design
A1 Dieste Velasco, Mª Isabel
K1 Fuzzy systems
K1 Machine learning
K1 Applications
K1 Analog circuits
K1 Desing
K1 Electrotecnia
K1 Electrical engineering
K1 Ingeniería mecánica
K1 Mechanical engineering
AB Simulation programs are widely used in the design of analog electronic circuits to analyze their behavior and to predict the response of a circuit to variations in the circuit components. A fuzzy inference system (FIS) in combination with these simulation tools can be applied to identify both the main and interaction effects of circuit parameters on the response variables, which can help to optimize them. This paper describes an application of fuzzy inference systems to modeling the behavior of analog electronic circuits for further optimization. First, a Monte Carlo analysis, generated from the tolerances of the circuit components, is performed. Once the Monte Carlo results are obtained for each of the response variables, the fuzzy inference systems are generated and then optimized using a particle swarm optimization (PSO) algorithm. These fuzzy inference systems are used to determine the influence of the circuit components on the response variables and to select them to optimize the amplifier design. The methodology proposed in this study can be used as the basis for optimizing the design of similar analog electronic circuits.
PB MDPI
YR 2021
FD 2021-09
LK http://hdl.handle.net/10259/8681
UL http://hdl.handle.net/10259/8681
LA eng
DS Repositorio Institucional de la Universidad de Burgos
RD 22-dic-2024