scholarly journals Interactions and Optimizations Analysis between Stiffness and Workspace of 3-UPU Robotic Mechanism

2017 ◽  
Vol 17 (2) ◽  
pp. 83-92 ◽  
Author(s):  
Dan Zhang ◽  
Bin Wei
Keyword(s):  
Differential Evolution ◽  
Pareto Front ◽  
Robotic System ◽  
Objective Functions ◽  
Stroke Patients ◽  
Walking Machine ◽  
The One ◽  
Translational Stiffness ◽  
Directional Stiffness ◽  
Changing Tendency

Abstract The interactions between stiffness and workspace performances are studied. The stiffness in x, y and z directions as well as the workspace of a 3-UPU mechanism are studied and optimized. The stiffness of the robotic system in every single moveable direction is measured and analyzed, and it is observed that in the case where one tries to make the x and y translational stiffness larger, the z directional stiffness will be reduced, i.e. the x and y translational stiffness contradicts with the one in z direction. Subsequently, the objective functions for the summation of the x and y translational stiffness and z directional stiffness are established and they are being optimized simultaneously. However, we later found that these two objectives are not in the same scale; a normalization of the objectives is thus taken into consideration. Meanwhile, the robotic system’s workspace is studied and optimized. Through comparing the stiffness landscape and the workspace volume landscape, it is also observed that the z translational stiffness shows the same changing tendency with the workspace volume’s changing tendency while the x and y translational stiffness shows the opposite changing tendency compared to the workspace volume’s. Via employing the Pareto front theory and differential evolution, the summation of the x and y translational stiffness and the volume of the workspace are being simultaneously optimized. Finally, the mechanism is employed to synthesize an exercise-walking machine for stroke patients.

scholarly journals An Analytical Study in Multi-physics and Multi-criteria Shape Optimization

2021 ◽  
Author(s):  
Hanno Gottschalk ◽  
Marco Reese
Keyword(s):  
Shape Optimization ◽  
Physical System ◽  
Pareto Front ◽  
Optimization Problem ◽  
Analytical Study ◽  
Static Pressure ◽  
Hausdorff Metric ◽  
Objective Functions ◽  
Hölder Continuous ◽  
Turbine Vane

AbstractA simple multi-physical system for the potential flow of a fluid through a shroud, in which a mechanical component, like a turbine vane, is placed, is modeled mathematically. We then consider a multi-criteria shape optimization problem, where the shape of the component is allowed to vary under a certain set of second-order Hölder continuous differentiable transformations of a baseline shape with boundary of the same continuity class. As objective functions, we consider a simple loss model for the fluid dynamical efficiency and the probability of failure of the component due to repeated application of loads that stem from the fluid’s static pressure. For this multi-physical system, it is shown that, under certain conditions, the Pareto front is maximal in the sense that the Pareto front of the feasible set coincides with the Pareto front of its closure. We also show that the set of all optimal forms with respect to scalarization techniques deforms continuously (in the Hausdorff metric) with respect to preference parameters.

An enhanced surrogate-assisted differential evolution for constrained optimization problems

2021 ◽  
Author(s):  
Rafael de Paula Garcia ◽  
Beatriz Souza Leite Pires de Lima ◽  
Afonso Celso de Castro Lemonge ◽  
Breno Pinheiro Jacob
Keyword(s):  
Differential Evolution ◽  
Optimization Problems ◽  
Optimization Procedure ◽  
Nearest Neighbors ◽  
Engineering Optimization ◽  
Optimal Solutions ◽  
Objective Functions ◽  
Constrained Optimization Problems ◽  
Engineering Problems ◽  
Complex Engineering

Abstract The application of Evolutionary Algorithms (EAs) to complex engineering optimization problems may present difficulties as they require many evaluations of the objective functions by computationally expensive simulation procedures. To deal with this issue, surrogate models have been employed to replace those expensive simulations. In this work, a surrogate-assisted evolutionary optimization procedure is proposed. The procedure combines the Differential Evolution method with a Anchor -nearest neighbors ( –NN) similarity-based surrogate model. In this approach, the database that stores the solutions evaluated by the exact model, which are used to approximate new solutions, is managed according to a merit scheme. Constraints are handled by a rank-based technique that builds multiple separate queues based on the values of the objective function and the violation of each constraint. Also, to avoid premature convergence of the method, a strategy that triggers a random reinitialization of the population is considered. The performance of the proposed method is assessed by numerical experiments using 24 constrained benchmark functions and 5 mechanical engineering problems. The results show that the method achieves optimal solutions with a remarkably reduction in the number of function evaluations compared to the literature.

Chaotic Differential-Evolution-Based Fuzzy Contrast Stretching Method

2018 ◽  
pp. 71-94 ◽  
Author(s):  
Krishna Gopal Dhal ◽  
Sanjoy Das
Keyword(s):  
Differential Evolution ◽  
Objective Function ◽  
Quality Index ◽  
Color Images ◽  
Consumer Electronics ◽  
Grey Level ◽  
Swarm Optimization ◽  
Local Variance ◽  
The One ◽  
Contrast Stretching

This study concentrates to develop one novel parameterized Bi-Histogram Fuzzy Contrast Stretching (BHFCS) method for enhancing the contrast of the grey level as well as color images properly. The parameters of this method have been optimized by employing one modified Chaotic Differential Evolution (CDE) with the combined assistance of Fractal Dimension (FD) and Quality Index based on Local Variance (QILV) as objective function. Experimental results prove that the modified DE gives better result than particle swarm optimization (PSO), genetic algorithm (GA) and traditional DE in this enhancement domain and the used objective function is also very useful to preserve the image's original brightness which is the one of the main criterion of the consumer electronics field.

Multi-Objective Geometric Optimization of Elliptical-Toothed Gerotor Pumps for Kinematics and Wear by Genetic Algorithm

2018 ◽  
Author(s):  
Andrew J. Robison ◽  
Andrea Vacca
Keyword(s):  
Genetic Algorithm ◽  
Pareto Front ◽  
Adhesive Wear ◽  
Geometric Optimization ◽  
Objective Functions ◽  
Computationally Efficient ◽  
Nsga Ii ◽  
Generation Algorithm ◽  
Flow Ripple ◽  
Gerotor Pumps

A computationally efficient gerotor gear generation algorithm has been developed that creates elliptical-toothed gerotor gear profiles, identifies conditions to guarantee a feasible geometry, evaluates several performance objectives, and is suitable to use for geometric optimization. Five objective functions are used in the optimization: minimize pump size, flow ripple, adhesive wear, subsurface fatigue (pitting), and tooth tip leakage. The gear generation algorithm is paired with the NSGA-II optimization algorithm to minimize each of the objective functions subject to the constraints to define a feasible geometry. The genetic algorithm is run with a population size of 1000 for a total of 500 generations, after which a clear Pareto front is established and displayed. A design has been selected from the Pareto front which is a good compromise between each of the design objectives and can be scaled to any desired displacement. The results of the optimization are also compared to two profile geometries found in literature. Two alternative geometries are proposed that offer much lower adhesive wear while respecting the size constraints of the published profiles and are thought to be an improvement in design.

Shape Optimization of Microchannels Using Surrogate Modelling

2018 ◽  
Author(s):  
Muhammad Ansab Ali ◽  
Tariq S. Khan ◽  
Saqib Salam ◽  
Ebrahim Al Hajri
Keyword(s):  
Shape Optimization ◽  
Heat Sink ◽  
Pareto Front ◽  
Sampling Method ◽  
Design Space ◽  
Latin Hypercube Sampling ◽  
Optimum Shape ◽  
Microchannel Heat Sink ◽  
Objective Functions ◽  
Computational Resources

To minimize the computational and optimization time, a numerical simulation of 3D microchannel heat sink was performed using surrogate model to achieve the optimum shape. Latin hypercube sampling method was used to explore the design space and to construct the model. The accuracy of the model was evaluated using statistical methods like coefficient of multiple determinations and root mean square error. Thermal resistance and pressure drop being conflicting objective functions were selected to optimize the geometric parameters of the microchannel. Multi objective shape optimization of design was conducted using genetic algorithm and the optimum design solutions are presented in the Pareto front. The application of the surrogate methods has predicted the performance of the heat sink with the sufficient accuracy employing significantly lower computational resources.

Mathematical Modeling and Multi-Objective Optimization of a Mini-Channel Heat Exchanger Via Genetic Algorithm

2013 ◽  
Vol 5 (3) ◽  
Author(s):  
Tommaso Selleri ◽  
Behzad Najafi ◽  
Fabio Rinaldi ◽  
Guido Colombo
Keyword(s):  
Genetic Algorithm ◽  
Heat Exchanger ◽  
Multiobjective Optimization ◽  
Pareto Front ◽  
Optimization Procedure ◽  
Design Parameters ◽  
Geometrical Parameters ◽  
Objective Functions ◽  
Pressure Drops ◽  
Overall Heat Transfer Coefficient

In the present paper a mathematical model for a mini-channel heat exchanger is proposed. Multiobjective optimization using genetic algorithm is performed in the next step in order to obtain a set of geometrical design parameters, leading to minimum pressure drops and maximum overall heat transfer coefficient. Multiobjective optimization procedure provides a set of optimal solutions, called Pareto front, each of which is a trade-off between the objective functions and can be freely selected by the user according to the specifications of the project. A sensitivity analysis is also carried out to study the effects of different geometrical parameters on the considered functions. The whole system has been modeled based on advanced experimental correlations in matlab environment using a modular approach.

scholarly journals Multi-Objective Design Optimization of the Leg Mechanism for a Piping Inspection Robot

2014 ◽  
Author(s):  
Renaud Henry ◽  
Damien Chablat ◽  
Mathieu Porez ◽  
Frédéric Boyer ◽  
Daniel Kanaan
Keyword(s):  
Nuclear Power ◽  
Pareto Front ◽  
Design Parameters ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Dimensional Synthesis ◽  
Force Factor ◽  
Multi Objective ◽  
Inspection Robot ◽  
Contact Points

This paper addresses the dimensional synthesis of an adaptive mechanism of contact points ie a leg mechanism of a piping inspection robot operating in an irradiated area as a nuclear power plant. This studied mechanism is the leading part of the robot sub-system responsible of the locomotion. Firstly, three architectures are chosen from the literature and their properties are described. Then, a method using a multi-objective optimization is proposed to determine the best architecture and the optimal geometric parameters of a leg taking into account environmental and design constraints. In this context, the objective functions are the minimization of the mechanism size and the maximization of the transmission force factor. Representations of the Pareto front versus the objective functions and the design parameters are given. Finally, the CAD model of several solutions located on the Pareto front are presented and discussed.

Crank Arrangement on the Dynamics of a Quadruped Walking Machine

2015 ◽  
Vol 764-765 ◽  
pp. 213-217
Author(s):  
Fu Chen Chen ◽  
Shang Chen Wu ◽  
Yung Cheng Chen
Keyword(s):  
Dynamic Response ◽  
Dynamic Characteristics ◽  
Pitch Angle ◽  
Walking Machine ◽  
Design And Optimization ◽  
Future Design ◽  
Walking Machines ◽  
The One

The purpose of this study is to investigate the effect of crank arrangement on the dynamics of a quadruped walking machine. The dynamic characteristics of the walking machine, including the stance leg sequence, pitch angle and dynamic response of the quadruped walking machine are investigated and compared with the existing design. The results show that the phrase angle between front and rear legs on the same side should be 0o or 90o and the one between the legs on the different sides should be 180o. The results of this study can serve as a reference for future design and optimization of quadruped walking machines.

Multi-Objective Optimization of a 2-DoF Purely Translational Parallel Manipulator

2011 ◽  
Vol 317-319 ◽  
pp. 794-798
Author(s):  
Zhi Bin Li ◽  
Yun Jiang Lou ◽  
Yong Sheng Zhang ◽  
Ze Xiang Li
Keyword(s):  
Genetic Algorithm ◽  
Kinematic Analysis ◽  
Parallel Manipulator ◽  
Pareto Front ◽  
Parallel Robot ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Evolution Algorithm

The paper addresses the multi-objective optimization of a 2-DoF purely translational parallel manipulator. The kinematic analysis of the Proposed T2 parallel robot is introduced briefly. The objective functions are optimized simultaneously to improve Regular workspace Share (RWS) and Global Conditioning Index (GCI). A Multi-Objective Evolution Algorithm (MOEA) based on the Control Elitist Non-dominated Sorting Genetic Algorithm (controlled ENSGA-II) is used to find the Pareto front. The optimization results show that this method is efficient. The parallel manipulator prototype is also exhibited here.

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