Global Dynamic Optimization of Linear Hybrid Systems

Author(s):  
C. K. Lee ◽  
P. I. Barton
2006 ◽  
Vol 110 (3) ◽  
pp. 971-976 ◽  
Author(s):  
Adam B. Singer ◽  
James W. Taylor ◽  
Paul I. Barton ◽  
William H. Green

2015 ◽  
Vol 789-790 ◽  
pp. 723-734
Author(s):  
Xing Guo Lu ◽  
Ming Liu ◽  
Min Xiu Kong

This work tends to deal with the multi-objective dynamic optimization problem of a three translational degrees of freedom parallel robot. Two global dynamic indices are proposed as the objective functions for the dynamic optimization: the index of dynamic dexterity, the index describing the dynamic fluctuation effects. The length of the linkages and the circumradius of the platforms were chosen as the design variables. A multi-objective optimal design problem, including constrains on the actuating and passive joint angle limits and geometrical interference is then formulated to find the Pareto solutions for the robot in a desired workspace. The Non-dominated Sorting Genetic Algorithm (NSGA-II) is adopted to solve the constrained nonlinear multi-objective optimization problem. The simulation results obtained shows that the robot can achieve better dynamic dexterity and less dynamic fluctuation simultaneously after the optimization.


2014 ◽  
Vol 8 (1) ◽  
pp. 1 ◽  
Author(s):  
Gundián M de Hijas-Liste ◽  
Edda Klipp ◽  
Eva Balsa-Canto ◽  
Julio R Banga

2017 ◽  
Vol 33 (2) ◽  
pp. 297-310 ◽  
Author(s):  
Eunice Blanchard ◽  
Ryan Loxton ◽  
Volker Rehbock

2020 ◽  
Vol 77 (3) ◽  
pp. 487-512
Author(s):  
Ishan Bajaj ◽  
M. M. Faruque Hasan

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