TY - GEN
T1 - Synthesis of Planar Linkages Using Optimization Methods
AU - Martínez, Manuel
AU - Venero, Sebastian
AU - Cancán, Sergio
AU - Quino, Gustavo
AU - Alegria, Elvis J.
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2022
Y1 - 2022
N2 - This paper analyzes and discusses the main characteristics of four optimization methods used in the synthesis of planar mechanisms. Particularities of the gradient-free Nelder-Mead, gradient-based local optimization, genetic algorithm for global optimization, and the particle swarm optimization methods are discussed and applied to the synthesis of restricted and unrestricted four-bar mechanism, which is the most popular and is usually present in more complex mechanisms, with a simple and smooth desired trajectory, and a more complicated six-bar with desired points throughout the crank domain and with a complex speed requirement. This paper does not intend to establish a comparison on which one is the best, which is an ambitious and arduous task to demonstrate but rather guides the designer to a correct selection of optimization methods considering the availability of the gradient and the computational requirements of the problem. Finally, some criteria for choosing a suitable synthesis method, depending on the problem requirements, are proposed.
AB - This paper analyzes and discusses the main characteristics of four optimization methods used in the synthesis of planar mechanisms. Particularities of the gradient-free Nelder-Mead, gradient-based local optimization, genetic algorithm for global optimization, and the particle swarm optimization methods are discussed and applied to the synthesis of restricted and unrestricted four-bar mechanism, which is the most popular and is usually present in more complex mechanisms, with a simple and smooth desired trajectory, and a more complicated six-bar with desired points throughout the crank domain and with a complex speed requirement. This paper does not intend to establish a comparison on which one is the best, which is an ambitious and arduous task to demonstrate but rather guides the designer to a correct selection of optimization methods considering the availability of the gradient and the computational requirements of the problem. Finally, some criteria for choosing a suitable synthesis method, depending on the problem requirements, are proposed.
KW - Genetic algorithms
KW - Gradient descent
KW - Mechanisms synthesis
KW - Nelder-Mead simplex
KW - Particle swarm optimization
UR - http://www.scopus.com/inward/record.url?scp=85135064289&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-08545-1_57
DO - 10.1007/978-3-031-08545-1_57
M3 - Conference contribution
AN - SCOPUS:85135064289
SN - 9783031085444
T3 - Smart Innovation, Systems and Technologies
SP - 577
EP - 586
BT - Proceedings of the 7th Brazilian Technology Symposium, BTSym 2021 - Emerging Trends in Systems Engineering Mathematics and Physical Sciences
A2 - Iano, Yuzo
A2 - Saotome, Osamu
A2 - Kemper Vásquez, Guillermo Leopoldo
A2 - Cotrim Pezzuto, Claudia
A2 - Arthur, Rangel
A2 - Gomes de Oliveira, Gabriel
PB - Springer Science and Business Media Deutschland GmbH
T2 - 7th Brazilian Technology Symposium, BTSym 2021
Y2 - 8 November 2021 through 10 November 2021
ER -