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A Two-Stage Mono- and Multi-Objective Method for the Optimization of General UPS Parallel Manipulators

Author

Listed:
  • Alejandra Ríos

    (Instituto Politécnico Nacional, ESIME Ticomán, Mexico City 07738, Mexico)

  • Eusebio E. Hernández

    (Instituto Politécnico Nacional, ESIME Ticomán, Mexico City 07738, Mexico
    These authors contributed equally to this work.)

  • S. Ivvan Valdez

    (CONACYT, Centro de Investigación en Ciencias de Información Geoespacial, CENTROGEO A.C., Querétaro 76703, Mexico
    These authors contributed equally to this work.)

Abstract

This paper introduces a two-stage method based on bio-inspired algorithms for the design optimization of a class of general Stewart platforms. The first stage performs a mono-objective optimization in order to reach, with sufficient dexterity, a regular target workspace while minimizing the elements’ lengths. For this optimization problem, we compare three bio-inspired algorithms: the Genetic Algorithm (GA), the Particle Swarm Optimization (PSO), and the Boltzman Univariate Marginal Distribution Algorithm (BUMDA). The second stage looks for the most suitable gains of a Proportional Integral Derivative (PID) control via the minimization of two conflicting objectives: one based on energy consumption and the tracking error of a target trajectory. To this effect, we compare two multi-objective algorithms: the Multiobjective Evolutionary Algorithm based on Decomposition (MOEA/D) and Non-dominated Sorting Genetic Algorithm-III (NSGA-III). The main contributions lie in the optimization model, the proposal of a two-stage optimization method, and the findings of the performance of different bio-inspired algorithms for each stage. Furthermore, we show optimized designs delivered by the proposed method and provide directions for the best-performing algorithms through performance metrics and statistical hypothesis tests.

Suggested Citation

  • Alejandra Ríos & Eusebio E. Hernández & S. Ivvan Valdez, 2021. "A Two-Stage Mono- and Multi-Objective Method for the Optimization of General UPS Parallel Manipulators," Mathematics, MDPI, vol. 9(5), pages 1-20, March.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:5:p:543-:d:510556
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