Optimal dimensioning of redundantly actuated mechanism for maximizing energy efficiency and workspace via Taguchi method

Abstract

A kinematic optimization of a redundantly actuated parallel mechanism is developed via the Taguchi method to maximize the sum of energy efficiency and workspace. In the optimization process, the energy consumption in a representative pathway of a predefined workspace is used as the performance index of the energy efficiency. The horizontal reach and stroke, and the vertical reach of mechanism, are used for the performance index of the workspace. The kinematic parameters of a chain that was added to the proposed non-redundantly actuated parallel mechanism as an extension to achieve redundant actuation are selected as the controllable factors. The velocity of the end-effector is considered to be a noise factor. Because the Taguchi method was originally used for robust optimization, we can improve the energy efficiency and workspace under various velocities for the end-effector. In the first stage of optimization, the number of controllable factors is reduced, and their correlations are eliminated using a response analysis. Quasi-optimized results are derived after the second stage of optimization. The optimized redundantly actuated parallel mechanism result is validated by comparing the energy efficiencies and workspaces of the original and optimal redundantly actuated parallel mechanisms.

Optimal trajectory planning considering optimal torque distribution of redundantly actuated parallel mechanism

“…Pt|c2 x and Pt|c2 y denote the x and y position due to the forward kinematics of chain 2, respectively. 20,21 θt|c1 and θt|c2 denote the rotated angle of the moving frame {T} as a result of the forward kinematics of chains 1 and 2, respectively.…”

Multi-Objective Optimization Design of 6-UPS Parallel Mechanism Based on Taguchi Method and Entropy-Weighted Gray Relational Analysis

“…It can mine the information of the whole parameter space through a little number of experiments to obtain the optimal solution of the experimental design [37,38]. Park et al [39] performed kinematic optimization of a redundantly driven parallel mechanism using the Taguchi method with the optimization objective of maximizing the total of energy efficiency and workspace. Wu et al [40] used the Taguchi method and Monte Carlo simulation method to optimize the 3-RRR parallel micro-movement platform iteratively and found the optimal geometric size of the flexure hinge.…”

Design and optimization of an elastic linkage quadruped robot based on workspace and tracking error

“…The optimization result shows that the maximum rotation angle of the thigh increased by 4.17%, the maximum lifting height of the wheel had improved by 65.53%, and the maximum driving force of the thigh and calf decreased by 25.5% and 12.58%, respectively. 15 In another study, addition, Park et al 16 conducted the kinematic parameter optimization of 2-DOF redundantly actuated parallel mechanism, for the purpose of maximizing the energy-saving effect and workspace. Sangrok Jin et al 17 performed optimal design to maximize the working distance of the underwater manipulators with the height difference.…”

“…15 In another study, addition, Park et al. 16 conducted the kinematic parameter optimization of 2-DOF redundantly actuated parallel mechanism, for the purpose of maximizing the energy-saving effect and workspace. Sangrok Jin et al.…”