Evolutionary Multiobjective Design Approach for Robust Balancing of the Shaking Force, Shaking Moment, and Torque under Uncertainties: Application to Robotic Manipulators

Ricardo Mejia-Rodriguez, Miguel Gabriel Villarreal-Cervantes (), Alejandro Rodríguez-Molina, José Humberto Pérez-Cruz and Víctor Manuel Silva-García
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Ricardo Mejia-Rodriguez: Centro de Innovación y Desarrollo Tecnológico en Cómputo, Instituto Politécnico Nacional, Mecatronic Section, Postgraduate Department, Mexico City 07700, Mexico
Miguel Gabriel Villarreal-Cervantes: Centro de Innovación y Desarrollo Tecnológico en Cómputo, Instituto Politécnico Nacional, Mecatronic Section, Postgraduate Department, Mexico City 07700, Mexico
Alejandro Rodríguez-Molina: Tecnológico Nacional de México/ IT de Tlalnepantla, Research and Postgraduate Division, Tlalnepantla de Baz 54070, Mexico
José Humberto Pérez-Cruz: Instituto Politécnico Nacional, ESIME Azcapotzalco, Sección de Estudios de Posgrado e Investigación, Mexico City 02250, Mexico
Víctor Manuel Silva-García: Centro de Innovación y Desarrollo Tecnológico en Cómputo, Instituto Politécnico Nacional, Mecatronic Section, Postgraduate Department, Mexico City 07700, Mexico

Mathematics, 2023, vol. 11, issue 8, 1-54

Abstract: In this paper, the environmental uncertainties are taken into account when designing a robotic manipulator to balance the shaking force, shaking moment, and torque. The proposed robust balancing design approach does not consider the probability distributions of the uncertainties and is addressed without dependence on specific trajectories. This is expressed as a nonlinear constrained multiobjective optimization problem in which the nominal performance in the time-independent terms of the shaking force balancing, the shaking moment balancing, and the torque delivery, as well as their three sensitivities to uncertainties, are simultaneously optimized to provide a set of link shapes that match link mass distributions in a single stage. The proposal is applied to a three-degree-of-freedom serial-parallel manipulator, and the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) is used to solve the associated problem. Comparative results with other design approaches reveal that the selected design achieves a suitable tradeoff in balancing the shaking force balancing, the shaking moment balancing, and the torque delivery and their sensitivities, leading to a reduction in their values and variations under mass changes in the manipulator end-effector with different operating conditions (tasks).

Keywords: dynamic balancing; torque delivery; robustness; optimization; evolutionary computing (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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