Parametric reconfiguration improvement in non-iterative concurrent mechatronic design using an evolutionary-based approach

  • Authors:

  • Edgar Alfredo Portilla-Flores;Efrén Mezura-Montes;Jaime Alvarez-Gallegos;Carlos Artemio Coello-Coello;Carlos Alberto Cruz-Villar;Miguel Gabriel Villarreal-Cervantes

  • Affiliations:

  • Mechatronic Section, Postgraduate Department, CIDETEC-IPN, Av. Juan de Dios Bátiz s/n Esq. Miguel Othon de Mendizabal, Unidad Profesional Adolfo López Mateos, C.P. 07700, Mexico D.F., Me ...;Laboratorio Nacional de Informática Avanzada (LANIA A.C.), Rébsamen 80, Centro C.P. 91000, Xalapa, Veracruz, Mexico;Mechatronic Section, Electrical Engineering Department, Cinvestav-IPN, Av. Instituto Politécnico Nacional 2508, Col. San Pedro Zacatenco, C.P. 07360, Mexico D.F., Mexico;Computer Science Department (Evolutionary Computation Group), Cinvestav-IPN, Av.Instituto Politécnico Nacional 2508, Col. San Pedro Zacatenco, C.P. 07360, Mexico D.F., Mexico;Mechatronic Section, Electrical Engineering Department, Cinvestav-IPN, Av. Instituto Politécnico Nacional 2508, Col. San Pedro Zacatenco, C.P. 07360, Mexico D.F., Mexico;Mechatronic Section, Postgraduate Department, CIDETEC-IPN, Av. Juan de Dios Bátiz s/n Esq. Miguel Othon de Mendizabal, Unidad Profesional Adolfo López Mateos, C.P. 07700, Mexico D.F., Me ...

  • Venue:
  • Engineering Applications of Artificial Intelligence
  • Year:
  • 2011

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Abstract

Parametric reconfiguration plays a key role in non-iterative concurrent design of mechatronic systems. This is because it allows the designer to select, among different competitive solutions, the most suitable without sacrificing sub-optimal characteristics. This paper presents a method based on an evolutionary algorithm to improve the parametric reconfiguration feature in the optimal design of a continuously variable transmission and a five-bar parallel robot. The approach considers a solution-diversity mechanism coupled with a memory of those sub-optimal solutions found during the process. Furthermore, a constraint-handling mechanism is added to bias the search to the feasible region of the search space. Differential Evolution is utilized as the search algorithm. The results obtained in a set of five experiments performed per each mechatronic system show the effectiveness of the proposed approach.