An optimum design procedure for both serial and parallel manipulators

2007 ◽  
Vol 221 (7) ◽  
pp. 829-843 ◽  
Author(s):  
G Carbone ◽  
E Ottaviano ◽  
M Ceccarelli
Keyword(s):  
Optimization Problem ◽  
Design Procedure ◽  
Parallel Manipulators ◽  
Optimality Criteria ◽  
Design Stage ◽  
Multi Objective Optimization ◽  
Numerical Examples ◽  
Design Optimality ◽  
Basic Performance ◽  
Alternative Solutions

Serial and parallel manipulators can be used in different manipulative tasks when their peculiarities in kinematic and dynamic behaviours are properly considered from the design stage. The basic performance in workspace, mobility constraints, and stiffness makes them alternative solutions and not competitive manipulator chains. Thus, it is convenient to deduce a common design procedure that considers common design criteria, but specific numerical evaluations. In this paper, a multi-objective optimization problem has been proposed to formulate a unique design procedure that takes into account the contradicting design optimality criteria in terms of suitable general algorithms for workspace volumes, Jacobian matrices, and compliant displacements. Numerical examples are reported to show not just the feasibility but also the numerical efficiency of the proposed formulations.

scholarly journals An Optimal Design of Driving Mechanism in a 1 Degree of Freedom (d.o.f.) Anthropomorphic Finger

2005 ◽  
Vol 2 (2) ◽  
pp. 103-110 ◽  
Author(s):  
M. Ceccarelli ◽  
N. E. N. Rodríguez ◽  
G. Carbone ◽  
C. Lopez-Cajùn
Keyword(s):  
Optimization Problem ◽  
Evaluation Criteria ◽  
Design Procedure ◽  
Degree Of Freedom ◽  
Driving Mechanism ◽  
Multi Objective Optimization ◽  
Force Transmission ◽  
Driving Mechanisms ◽  
Finger Motion ◽  
Actuation Systems

Mechanisms can be used in finger design to obtain suitable actuation systems and to give stiff robust behavior in grasping tasks. The design of driving mechanisms for fingers has been attached at LARM in Cassino with the aim to obtain one degree of freedom actuation for an anthropomorphic finger. The dimensional design of a finger-driving mechanism has been formulated as a multi-objective optimization problem by using evaluation criteria for fundamental characteristics regarding with finger motion, grasping equilibrium and force transmission. The feasibility of the herein proposed optimum design procedure for a finger-driving mechanism has been tested by numerical examples that have been also used to enhance a prototype previously built at LARM in Cassino.

scholarly journals Over-Actuated Underwater Robots: Configuration Matrix Design and Perspectives

Sensors ◽  
2021 ◽  
Vol 21 (22) ◽  
pp. 7729
Author(s):  
Tho Dang ◽  
Lionel Lapierre ◽  
Rene Zapata ◽  
Benoit Ropars ◽  
Pascal Lepinay
Keyword(s):  
Goal Attainment ◽  
Optimization Problem ◽  
Design Procedure ◽  
Multi Objective Optimization ◽  
Performance Indices ◽  
Underwater Robots ◽  
Weighting Vector ◽  
Solution Design ◽  
Matrix Design ◽  
Configuration Designs

In general, for the configuration designs of underwater robots, the positions and directions of actuators (i.e., thrusters) are given and installed in conventional ways (known points, vertically, horizontally). This yields limitations for the capability of robots and does not optimize the robot’s resources such as energy, reactivity, and versatility, especially when the robots operate in confined environments. In order to optimize the configuration designs in the underwater robot field focusing on over-actuated systems, in the paper, performance indices (manipulability, energetic, reactive, and robustness indices) are introduced. The multi-objective optimization problem was formulated and analyzed. To deal with different objectives with different units, the goal-attainment method, which can avoid the difficulty of choosing a weighting vector to obtain a good balance among these objectives, was selected to solve the problem. A solution design procedure is proposed and discussed. The efficiency of the proposed method was proven by simulations and experimental results.

Optimality criteria for fuzzy-valued fractional multi-objective optimization problem

2018 ◽  
Vol 23 (19) ◽  
pp. 9049-9067 ◽  
Author(s):  
Deepika Agarwal ◽  
Pitam Singh ◽  
Xiong Li ◽  
Saru Kumari
Keyword(s):  
Optimization Problem ◽  
Optimality Criteria ◽  
Multi Objective Optimization ◽  
Multi Objective

scholarly journals Braille Block Detection via Multi-Objective Optimization from an Egocentric Viewpoint

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2775
Author(s):  
Tsubasa Takano ◽  
Takumi Nakane ◽  
Takuya Akashi ◽  
Chao Zhang
Keyword(s):  
Optimization Problem ◽  
Line Pair ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Optimization Framework ◽  
Visually Impaired People ◽  
Comprehensive Comparison ◽  
Basic Characteristics ◽  
Support Devices

In this paper, we propose a method to detect Braille blocks from an egocentric viewpoint, which is a key part of many walking support devices for visually impaired people. Our main contribution is to cast this task as a multi-objective optimization problem and exploits both the geometric and the appearance features for detection. Specifically, two objective functions were designed under an evolutionary optimization framework with a line pair modeled as an individual (i.e., solution). Both of the objectives follow the basic characteristics of the Braille blocks, which aim to clarify the boundaries and estimate the likelihood of the Braille block surface. Our proposed method was assessed by an originally collected and annotated dataset under real scenarios. Both quantitative and qualitative experimental results show that the proposed method can detect Braille blocks under various environments. We also provide a comprehensive comparison of the detection performance with respect to different multi-objective optimization algorithms.

Auto-sharing parameters for transfer learning based on multi-objective optimization

2021 ◽  
pp. 1-13
Author(s):  
Hailin Liu ◽  
Fangqing Gu ◽  
Zixian Lin
Keyword(s):  
Transfer Learning ◽  
Optimization Problem ◽  
Data Sets ◽  
Multi Objective Optimization ◽  
Particle Swarm Optimizer ◽  
Real World Data ◽  
Data Set ◽  
Target Task ◽  
Main Research ◽  
Multi Objective

Transfer learning methods exploit similarities between different datasets to improve the performance of the target task by transferring knowledge from source tasks to the target task. “What to transfer” is a main research issue in transfer learning. The existing transfer learning method generally needs to acquire the shared parameters by integrating human knowledge. However, in many real applications, an understanding of which parameters can be shared is unknown beforehand. Transfer learning model is essentially a special multi-objective optimization problem. Consequently, this paper proposes a novel auto-sharing parameter technique for transfer learning based on multi-objective optimization and solves the optimization problem by using a multi-swarm particle swarm optimizer. Each task objective is simultaneously optimized by a sub-swarm. The current best particle from the sub-swarm of the target task is used to guide the search of particles of the source tasks and vice versa. The target task and source task are jointly solved by sharing the information of the best particle, which works as an inductive bias. Experiments are carried out to evaluate the proposed algorithm on several synthetic data sets and two real-world data sets of a school data set and a landmine data set, which show that the proposed algorithm is effective.

Multi-objective optimization of a recuperative gas turbine cycle using non-dominated sorting genetic algorithm

2011 ◽  
Vol 225 (8) ◽  
pp. 1041-1051 ◽  
Author(s):  
H Sayyaadi ◽  
H R Aminian
Keyword(s):  
Genetic Algorithm ◽  
Gas Turbine ◽  
Heat Exchangers ◽  
Mixed Integer ◽  
Design Stage ◽  
Tube Length ◽  
Pareto Optimal ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Gas Turbine Cycle

A regenerative gas turbine cycle with two particular tubular recuperative heat exchangers in parallel is considered for multi-objective optimization. It is assumed that tubular recuperative heat exchangers and its corresponding gas cycle are in design stage simultaneously. Three objective functions including the purchased equipment cost of recuperators, the unit cost rate of the generated power, and the exergetic efficiency of the gas cycle are considered simultaneously. Geometric specifications of the recuperator including tube length, tube outside/inside diameters, tube pitch, inside shell diameter, outer and inner tube limits of the tube bundle and the total number of disc and doughnut baffles, and main operating parameters of the gas cycle including the compressor pressure ratio, exhaust temperature of the combustion chamber and the air mass flowrate are considered as decision variables. Combination of these objectives anddecision variables with suitable engineering and physical constraints (including NO x and CO emission limitations) comprises a set of mixed integer non-linear problems. Optimization programming in MATLAB is performed using one of the most powerful and robust multi-objective optimization algorithms, namely non-dominated sorting genetic algorithm. This approach is applied to find a set of Pareto optimal solutions. Pareto optimal frontier is obtained, and a final optimal solution is selected in a decision-making process.

The Equilibrium Cell-Based Smooth Finite Element Method for Shakedown Analysis of Structures

2019 ◽  
Vol 16 (05) ◽  
pp. 1840013 ◽  
Author(s):  
P. L. H. Ho ◽  
C. V. Le ◽  
T. Q. Chu
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Optimization Problem ◽  
Conic Programming ◽  
Equilibrium Equations ◽  
Shakedown Analysis ◽  
Numerical Examples ◽  
Elastic Stresses ◽  
Gauss Points ◽  
Element Method

This paper presents a novel equilibrium formulation, that uses the cell-based smoothed method and conic programming, for limit and shakedown analysis of structures. The virtual strains are computed using straining cell-based smoothing technique based on elements of discretized mesh. Fictitious elastic stresses are also determined within the framework of finite element method (CS-FEM)-based Galerkin procedure, and equilibrium equations for residual stresses are satisfied in an average sense at every cell-based smoothing cell. All constrains are imposed at only one point in the smoothing domains, instead of Gauss points as in a standard FEM-based procedure. The resulting optimization problem is then handled using the highly efficient solvers. Various numerical examples are investigated, and obtained solutions are compared with available results in the literature.

scholarly journals Multi-Objective Optimization of Autonomous Microgrids with Reliability Consideration

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4466
Author(s):  
Maël Riou ◽  
Florian Dupriez-Robin ◽  
Dominique Grondin ◽  
Christophe Le Loup ◽  
Michel Benne ◽  
...  
Keyword(s):  
Power Systems ◽  
Rural Areas ◽  
Energy System ◽  
Design Stage ◽  
Multi Objective Optimization ◽  
Renewable Energy Resources ◽  
Nsga Ii ◽  
Renewable Integration ◽  
Multi Objective ◽  
Trade Offs

Microgrids operating on renewable energy resources have potential for powering rural areas located far from existing grid infrastructures. These small power systems typically host a hybrid energy system of diverse architecture and size. An effective integration of renewable energies resources requires careful design. Sizing methodologies often lack the consideration for reliability and this aspect is limited to power adequacy. There exists an inherent trade-off between renewable integration, cost, and reliability. To bridge this gap, a sizing methodology has been developed to perform multi-objective optimization, considering the three design objectives mentioned above. This method is based on the non-dominated sorting genetic algorithm (NSGA-II) that returns the set of optimal solutions under all objectives. This method aims to identify the trade-offs between renewable integration, reliability, and cost allowing to choose the adequate architecture and sizing accordingly. As a case study, we consider an autonomous microgrid, currently being installed in a rural area in Mali. The results show that increasing system reliability can be done at the least cost if carried out in the initial design stage.

Bending Stiffener Design Through Structural Optimization

2009 ◽  
Author(s):  
Rafael Loureiro Tanaka ◽  
Lauro Massao Yamada da Silveira ◽  
Joa˜o Paulo Zi´lio Novaes ◽  
Eduardo Esterqui de Barros ◽  
Clo´vis de Arruda Martins
Keyword(s):  
Optimization Problem ◽  
Design Procedure ◽  
Complex Task ◽  
Load Case ◽  
Shear Forces ◽  
Design Variables ◽  
Curvilinear Coordinate ◽  
Regular Design ◽  
Curvature Deformation ◽  
Flexible Risers

Bending stiffeners are very important ancillary equipments of umbilicals or flexible risers, since they protect the lines from overbending. Their design however is a complex task, since many load cases must be taken into account; the structure itself has a section that is variable with curvilinear coordinate. To aid the designer in this task, optimization algorithms can be used to automate the search for the best design. In this work an optimization algorithm is applied to the design of the bending stiffener. First, a bending stiffener model is created, which is capable of simulating different load case conditions and provide, as output, results of interest such as maximum curvature, deformation along the stiffener, shear forces and so on. Then, a bending stiffener design procedure is written as an optimization problem and, for that, objective function, restrictions and design variables defined. Study cases were performed, comparing a regular design with its optimized counterpart, under varying conditions.

Optimization Problem of a Linear Induction Generator with a Liquid Working Fluid

2021 ◽  
Vol 64 (6) ◽  
pp. 16-21
Author(s):  
Konstantin Kim ◽  
◽  
Konstantin Kim ◽  
Andrey Vataev ◽  
◽  
...  
Keyword(s):  
Computer Technology ◽  
Optimization Problem ◽  
Magnetic System ◽  
Optimality Criteria ◽  
Working Fluid ◽  
Conducting Liquid ◽  
Calculation Algorithm ◽  
Linear Induction ◽  
Induction Generators ◽  
Calculation Results

We present the problem of optimization of cylindrical linear induction generators. The stator winding is located on the inner and outer cores of the magnetic system. The working fluid is a well-conducting liquid moving at a constant speed along the length of the channel. Since the generator is one of the elements of a complex installation the problem of optimizing it should be coordinated with a similar problem for the installation as a whole. This is done with the help the parameters common to all installation elements. Such parameters are the speed and flow rate of the working fluid. We describe the calculation algorithm with the use of computer technology. The efficiency and specific gravity of the generator are accepted as optimality criteria. The calculation results for a generator with the power of 20 MW are presented.

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