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Applied Mathematics and Mechanics

, Volume 40, Issue 1, pp 111–126 | Cite as

Particle swarm optimization-based algorithm of a symplectic method for robotic dynamics and control

  • Zhaoyue Xu
  • Lin DuEmail author
  • Haopeng Wang
  • Zichen Deng
Article
  • 64 Downloads

Abstract

Multibody system dynamics provides a strong tool for the estimation of dynamic performances and the optimization of multisystem robot design. It can be described with differential algebraic equations (DAEs). In this paper, a particle swarm optimization (PSO) method is introduced to solve and control a symplectic multibody system for the first time. It is first combined with the symplectic method to solve problems in uncontrolled and controlled robotic arm systems. It is shown that the results conserve the energy and keep the constraints of the chaotic motion, which demonstrates the efficiency, accuracy, and time-saving ability of the method. To make the system move along the pre-planned path, which is a functional extremum problem, a double-PSO-based instantaneous optimal control is introduced. Examples are performed to test the effectiveness of the double-PSO-based instantaneous optimal control. The results show that the method has high accuracy, a fast convergence speed, and a wide range of applications. All the above verify the immense potential applications of the PSO method in multibody system dynamics.

Key words

robotic dynamics multibody system symplectic method particle swarm optimization (PSO) algorithm instantaneous optimal control 

Chinese Library Classification

O313.7 

2010 Mathematics Subject Classification

70E55 

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Copyright information

© Shanghai University and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Zhaoyue Xu
    • 1
    • 2
  • Lin Du
    • 1
    • 3
    Email author
  • Haopeng Wang
    • 2
  • Zichen Deng
    • 3
    • 4
  1. 1.School of Natural and Applied ScienceNorthwestern Polytechnical UniversityXi’anChina
  2. 2.School of AeronauticsNorthwestern Polytechnical UniversityXi’anChina
  3. 3.Ministry of Industry and Information Technology (MIIT) Key Laboratory of Dynamics and Control of Complex SystemsNorthwestern Polytechnical UniversityXi’anChina
  4. 4.Department of Engineering MechanicsNorthwestern Polytechnical UniversityXi’anChina

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