Discretize-Then-Relax Approach For State Relaxactions In Global Dynamic Optimization

Computer Aided Chemical Engineering - 20th European Symposium on Computer Aided Process Engineering ◽

10.1016/s1570-7946(10)28072-0 ◽

2010 ◽

pp. 427-432 ◽

Cited By ~ 1

Author(s):

Ali M. Sahlodin ◽

Benoît Chachuat

Keyword(s):

Dynamic Optimization ◽

Global Dynamic

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Global Dynamic Optimization for Parameter Estimation in Chemical Kinetics

The Journal of Physical Chemistry A ◽

10.1021/jp0548873 ◽

2006 ◽

Vol 110 (3) ◽

pp. 971-976 ◽

Cited By ~ 62

Author(s):

Adam B. Singer ◽

James W. Taylor ◽

Paul I. Barton ◽

William H. Green

Keyword(s):

Parameter Estimation ◽

Chemical Kinetics ◽

Dynamic Optimization ◽

Global Dynamic

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Global Dynamic Optimization of Linear Hybrid Systems

Nonconvex Optimization and Its Applications - Frontiers in Global Optimization ◽

10.1007/978-1-4613-0251-3_16 ◽

2004 ◽

pp. 289-312 ◽

Cited By ~ 2

Author(s):

C. K. Lee ◽

P. I. Barton

Keyword(s):

Hybrid Systems ◽

Dynamic Optimization ◽

Global Dynamic

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Dynamic Optimization of a Three Translational Degrees of Freedom Parallel Robot Based on a Multi-Objective Genetic Algorithm

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.789-790.723 ◽

2015 ◽

Vol 789-790 ◽

pp. 723-734

Author(s):

Xing Guo Lu ◽

Ming Liu ◽

Min Xiu Kong

Keyword(s):

Genetic Algorithm ◽

Dynamic Optimization ◽

Degrees Of Freedom ◽

Optimization Problem ◽

Parallel Robot ◽

Nsga Ii ◽

Multi Objective ◽

Global Dynamic ◽

Design Variables ◽

Dynamic Fluctuation

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.

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