Force/motion transmissibility analysis and parameters optimization of hybrid mechanisms with prescribed workspace

Yu Sun, Gaoliang Peng, Kang Jin, Shiwei Liu, Paolo Gardoni, Zhixiong Li

Research output: Contribution to journalArticlepeer-review


Hybrid mechanisms have received growing interest and have been a widely used tool due to enlarged workspace and improved performance. Researchers have pay attention to optimization method of kinematic parameters which determine the kinematic performance. In order to evaluate the force/transmission performance for hybrid mechanism with prescribe workspace as constraint. This study proposes a transmission index (TI) for kinematic performance evaluation based on the power coefficient via screw theory. A customized algorithm based on genetic algorithm (GA) is presented to obtain the best parameters with prescribed workspace in which the kinematic performance makes sense. Particularly, a search strategy is given for quickly judging if the actual workspace could cover the prescribed workspace in a customized order. The GA-based optimization approach is applied to produce an optimal design of a mechanism consists of a 3- PPR planar PM and PS-2UPS-RPS PM with actuation redundancy. The result indicates that the mechanism has better motion/force transmission performance under the optimized parameters. In addition, the optimization algorithm is quiet practical with good convergence.

Original languageEnglish (US)
Pages (from-to)264-277
Number of pages14
JournalEngineering Analysis with Boundary Elements
StatePublished - Jun 2022


  • Actuation redundancy
  • Genetic algorithm
  • Hybrid mechanism
  • Motion/force transmission
  • Parameter optimization

ASJC Scopus subject areas

  • Analysis
  • Engineering(all)
  • Computational Mathematics
  • Applied Mathematics


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