On the Optimum Synthesis of Six-Bar Linkages Using Differential Evolution and the Geometric Centroid of Precision Positions Technique

2003 ◽  
Author(s):  
D. Koladiya ◽  
P. S. Shiakolas ◽  
J. Kebrle
Keyword(s):  
Differential Evolution ◽  
Evolutionary Optimization ◽  
Penalty Functions ◽  
Optimization Scheme ◽  
Constraint Violation ◽  
Initial Application ◽  
Optimum Synthesis ◽  
Design Variables ◽  
Transmission Angle ◽  
Accuracy Level

This paper presents the development of a methodology for the synthesis of six-bar dwell mechanisms combining Differential Evolution, an evolutionary optimization scheme, and the Geometric Centroid of Precision Positions technique for defining the initial bounds of the design variables. Two penalty functions are employed one for constraint violation and one for relative accuracy. The results of the initial application of this methodology were also used as “good initial guesses” for improving the desired accuracy level. The developed methodology is applied to the synthesis of six-bar linkages for dwell and dual-dwell mechanisms with prescribed timing and transmission angle constraints. The six-bar mechanism is synthesized using two different approaches: four-bar and extension to six-bar, direct six-bar. Results demonstrating the successful application of the developed methodology and the three approaches are presented.

scholarly journals Optimum Robot Design Based on Task Specifications Using Evolutionary Techniques and Kinematic, Dynamic, and Structural Constraints

2002 ◽  
Author(s):  
P. S. Shiakolas ◽  
D. Koladiya ◽  
J. Kebrle
Keyword(s):  
Genetic Algorithms ◽  
Differential Evolution ◽  
Cross Sections ◽  
Evolutionary Optimization ◽  
Robot Design ◽  
Structural Constraints ◽  
Link Length ◽  
Cross Sectional ◽  
Physical Constraints ◽  
Design Variables

In this paper, we discuss optimum robot design based on task specifications using evolutionary optimization approaches. The three evolutionary optimization approaches employed are Simple Genetic Algorithms, Genetic Algorithms with elitism, and Differential Evolution. These approaches were used for the optimum design of SCARA and articulated type manipulators. The objective function minimizes the torque required for the motion subject to deflection and physical constraints with the design variables being the physical characteristics of link (length and cross sectional area parameters). In this work, we experimented links with various cross sections. The main findings of this research are that the differential evolution converges quickly, requires significantly less number of iterations and achieves better results.

Evolutionary Based Optimal Synthesis of Four-Bar Mechanisms

2003 ◽  
Author(s):  
D. Koladiya ◽  
P. S. Shiakolas ◽  
J. Kebrle
Keyword(s):  
Optimization Techniques ◽  
Optimization Approach ◽  
Path Generation ◽  
Planar Mechanisms ◽  
Function Generation ◽  
Novel Technique ◽  
Optimum Synthesis ◽  
Design Variables ◽  
Accuracy Level ◽  
And Function

Graphical and analytical syntheses have been well applied to path, motion and function generation of planar mechanisms. Optimization techniques in common, require “good initial guesses” and do not necessarily converge to a solution. This paper presents a methodology to synthesize mechanisms employing an evolutionary optimization approach technique known as Differential Evolution. The initial bounds for the design variables are defined automatically using a newly developed and novel technique called the Geometric Centroid of Precision Points. Optimum synthesis of four-bar linkages for path generation with user defined accuracy level at required precision points is discussed.

scholarly journals Autonomous Planning of Multigravity-Assist Trajectories with Deep Space Maneuvers Using a Differential Evolution Approach

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Ossama Abdelkhalik
Keyword(s):  
Genetic Algorithms ◽  
Differential Evolution ◽  
Optimization Problems ◽  
Optimal Number ◽  
Deep Space ◽  
Biologically Inspired ◽  
Autonomous Planning ◽  
Design Variables ◽  
Planning Problems ◽  
Evolution Approach

The biologically inspired concept of hidden genes has been recently introduced in genetic algorithms to solve optimization problems where the number of design variables is variable. In multigravity-assist trajectories, the hidden genes genetic algorithms demonstrated success in searching for the optimal number of swing-bys and the optimal number of deep space maneuvers. Previous investigations in the literature for multigravity-assist trajectory planning problems show that the standard differential evolution is more effective than the standard genetic algorithms. This paper extends the concept of hidden genes to differential evolution. The hidden genes differential evolution is implemented in optimizing multigravity-assist space trajectories. Case studies are conducted, and comparisons to the hidden genes genetic algorithms are presented in this paper.

Dimensional synthesis of the Delta robot using transmission angle constraintsDimensional synthesis of the Delta robot using transmission angle constraints

Robotica ◽  
2011 ◽  
Vol 30 (3) ◽  
pp. 343-349 ◽  
Author(s):  
LiMin Zhang ◽  
JiangPing Mei ◽  
XueMan Zhao ◽  
Tian Huang
Keyword(s):  
Dynamic Performance ◽  
Volume Ratio ◽  
Dimensional Synthesis ◽  
Performance Constraints ◽  
Global Dynamic ◽  
Design Variables ◽  
Transmission Angle ◽  
Pressure Transmission ◽  
Delta Robot ◽  
And Performance

SUMMARYThis paper deals with dynamic dimensional synthesis of the Delta robot using the pressure/transmission angle constraints. Two types of pressure/transmission angles are defined, with which the direct and indirect singularities can be identified in a straightforward manner. Two novel global dynamic metrics are proposed for minimisation, which are associated respectively with the inertial and centrifuge/Coriolis components of the driving torque. Various geometrical and performance constraints are taken into account in terms of workspace/machine volume ratio, pressure/transmission angles, etc. The effects of pressure/transmission angle constraints on the feasible domain of design variables are investigated in depth via an example, and a set of optimised dimensional parameters is obtained for achieving a good kinematic and dynamic performance throughout the entire task workspace.

Optimization of shape to minimize stress concentration

1975 ◽  
Vol 10 (2) ◽  
pp. 63-70 ◽  
Author(s):  
A Francavilla ◽  
C V Ramakrishnan ◽  
O C Zienkiewicz
Keyword(s):  
Stress Concentration ◽  
Unconstrained Minimization ◽  
Penalty Functions ◽  
Design Parameters ◽  
Stress Concentrations ◽  
Design Variables ◽  
Side Constraints

The problem of minimizing stress concentrations in machinery components is formulated as one of unconstrained minimization by incorporating all ‘side’ constraints on design variables by use of penalty functions. Design parameters describing the transition are determined for an optimal fillet in a tension bar, as well as for a piston-rod ‘eye’. The procedure is generally applicable.

Integrated Mechanical and Thermodynamic Optimization of an Engine Linkage Using a Multi-Objective Genetic Algorithm

2015 ◽  
Vol 137 (2) ◽  
Author(s):  
Thomas A. Sullivan ◽  
James D. van de ven ◽  
William F. Northrop ◽  
Kieran McCabe
Keyword(s):  
Optimization Problem ◽  
Combustion Engine ◽  
Simultaneous Optimization ◽  
Thermodynamic Efficiency ◽  
Nsga Ii ◽  
Multi Objective Genetic Algorithm ◽  
Design Variables ◽  
Transmission Angle ◽  
Combustion Simulation ◽  
Kinematic Optimization

In order to improve the thermodynamic efficiency of an internal combustion engine (ICE), a Stephenson-III six-bar linkage is optimized to serve as a replacement for the traditional slider–crank. Novel techniques are presented for formulating the design variables in the kinematic optimization that guarantee satisfaction of the Grashof condition and of transmission angle requirements without the need for an explicit constraint function. Additionally, a nested generalization of the popular NSGA-II algorithm is presented that allows simultaneous optimization of the kinematic, dynamic, and thermodynamic properties of the mechanism. This approach successfully solves the complex six-objective optimization problem, with challenges for future refinement including improvement of the combustion simulation to attain better accuracy without prohibitive computational expense.

scholarly journals A global optimization paradigm based on change of measures

2015 ◽  
Vol 2 (7) ◽  
pp. 150123 ◽  
Author(s):  
Saikat Sarkar ◽  
Debasish Roy ◽  
Ram Mohan Vasu
Keyword(s):  
Global Optimization ◽  
Random Perturbation ◽  
Evolutionary Optimization ◽  
Global Optimum ◽  
Global Search ◽  
Design Variables ◽  
Change Of Measures ◽  
Basic Ideas ◽  
Set Up ◽  
Optimization Schemes

A global optimization framework, COMBEO (Change Of Measure Based Evolutionary Optimization), is proposed. An important aspect in the development is a set of derivative-free additive directional terms, obtainable through a change of measures en route to the imposition of any stipulated conditions aimed at driving the realized design variables (particles) to the global optimum. The generalized setting offered by the new approach also enables several basic ideas, used with other global search methods such as the particle swarm or the differential evolution, to be rationally incorporated in the proposed set-up via a change of measures. The global search may be further aided by imparting to the directional update terms additional layers of random perturbations such as ‘scrambling’ and ‘selection’. Depending on the precise choice of the optimality conditions and the extent of random perturbation, the search can be readily rendered either greedy or more exploratory. As numerically demonstrated, the new proposal appears to provide for a more rational, more accurate and, in some cases, a faster alternative to many available evolutionary optimization schemes.

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