Velocity Effects on Robotic Manipulator Dynamic Performance

2006 ◽  
Vol 128 (6) ◽  
pp. 1236-1245 ◽  
Author(s):  
Alan P. Bowling ◽  
ChangHwan Kim
Keyword(s):  
Quadratic Forms ◽  
Degrees Of Freedom ◽  
Optimization Problem ◽  
Dynamic Performance ◽  
Optimal Solution ◽  
Optimization Methods ◽  
Optimization Techniques ◽  
End Effector ◽  
Coriolis Forces ◽  
Torque Curve

This article explores the effect that velocities have on a nonredundant robotic manipulator’s ability to accelerate its end-effector, as well as to apply forces/moments to the environment at the end-effector. This work considers velocity forces, including Coriolis forces, and the reduction of actuator torque with rotor velocity described by the speed-torque curve, at a particular configuration of a manipulator. The focus here is on nonredundant manipulators with as many actuators as degrees-of-freedom. Analysis of the velocity forces is accomplished using optimization techniques, where the optimization problem consists of an objective function and constraints which are all purely quadratic forms, yielding a nonconvex problem. Dialytic elimination is used to find the globally optimal solution to this problem. The proposed method does not use iterative numerical optimization methods. The PUMA 560 manipulator is used as an example to illustrate this methodology. The methodology provides an analytical analysis of the velocity forces which insures that the globally optimal solution to the associated optimization problem is found.

Influence of End-Effector Velocities on Robotic Manipulator Dynamic Performance: An Analytical Approach

2003 ◽  
Author(s):  
ChangHwan Kim ◽  
Alan Bowling
Keyword(s):  
Quadratic Forms ◽  
Dynamic Performance ◽  
Optimal Solution ◽  
Problem Formulation ◽  
Optimization Techniques ◽  
Curve Analysis ◽  
Centrifugal Forces ◽  
End Effector ◽  
Nonconvex Problem ◽  
Torque Curve

This article explores the effect that end-effector velocities have on a nonredundant robotic manipulator’s ability to accelerate its end-effector as well as to apply forces/moments to the environment at the end-effector. The velocity effects considered here are the Coriolis and Centrifugal forces, and the reduction of actuator torque with rotor velocity, as described by the speed-torque curve. Analysis of these effects is accomplished using optimization techniques, where the problem formulation consists of a cost function and constraints which are all purely quadratic forms, yielding a nonconvex problem. An analytical solution, based on the dialytic elimination technique, is developed which guarantees that the globally optimal solution can be found. The PUMA 560 manipulator is used as an example to illustrate this methodology.

scholarly journals Optimal Reconfiguration of a Parallel Robot for Forward Singularities Avoidance in Rehabilitation Therapies. A Comparison via Different Optimization Methods

2020 ◽  
Vol 12 (14) ◽  
pp. 5803 ◽  
Author(s):  
Carlos Llopis-Albert ◽  
Francisco Valero ◽  
Vicente Mata ◽  
José L. Pulloquinga ◽  
Pau Zamora-Ortiz ◽  
...  
Keyword(s):  
Degrees Of Freedom ◽  
Local Minimum ◽  
Optimization Problem ◽  
Optimization Methods ◽  
Parallel Robot ◽  
Generalized Coordinates ◽  
Design Variables ◽  
Optimal Reconfiguration ◽  
Gradient Based ◽  
Parallel Kinematic

This paper presents an efficient algorithm for the reconfiguration of a parallel kinematic manipulator with four degrees of freedom. The reconfiguration of the parallel manipulator is posed as a nonlinear optimization problem where the design variables correspond to the anchoring points of the limbs of the robot on the fixed platform. The penalty function minimizes the forces applied by the actuators during a specific trajectory. Some constraints are imposed to avoid forward singularities and guarantee the feasibility of the active generalized coordinates for a certain trajectory. The results are compared with different optimization approaches with the aim of avoiding getting trapped into a local minimum and undergoing forward singularities. The comparison covers evolutionary algorithms, heuristics optimizers, multistrategy algorithms, and gradient-based optimizers. The proposed methodology has been successfully tested on an actual parallel robot for different trajectories.

A Survey of Nature-Inspired Algorithms With Application to Well Placement Optimization

2020 ◽  
pp. 32-45 ◽  
Author(s):  
Jahedul Islam ◽  
Pandian M. Vasant ◽  
Berihun Mamo Negash ◽  
Moacyr Bartholomeu Laruccia ◽  
Myo Myint
Keyword(s):  
Optimization Problem ◽  
Optimization Methods ◽  
Optimization Techniques ◽  
Economic Factors ◽  
Well Placement ◽  
Field Development ◽  
Placement Optimization ◽  
Well Placement Optimization ◽  
Nature Inspired Algorithms ◽  
Metaheuristic Techniques

Well placement optimization is one of the major challenging factors in the field development process in the oil and gas industry. This chapter aims to survey prominent metaheuristic techniques, which solve well the placement optimization problem. The well placement optimization problem is considered as high dimensional, discontinuous, and multi-model optimization problem. Moreover, the computational expenses further complicate the issue. Over the last decade, both gradient-based and gradient-free optimization methods were implemented. Gradient-free optimization, such as the particle swarm optimization, genetic algorithm, is implemented in this area. These optimization techniques are utilized as standalone or as the hybridization of optimization methods to maximize the economic factors. In this chapter, the authors survey the two most popular nature-inspired metaheuristic optimization techniques and their application to maximize the economic factors.

Evaluation of global optimization methods for conceptual rainfall-runoff model calibration

1997 ◽  
Vol 36 (5) ◽  
pp. 53-60 ◽  
Author(s):  
V. A. Cooper ◽  
V. T. V. Nguyen ◽  
J. A. Nicell
Keyword(s):  
Global Optimization ◽  
Optimal Solution ◽  
Optimization Methods ◽  
Global Optimum ◽  
Hydrologic Model ◽  
Optimization Techniques ◽  
Model Parameters ◽  
Rainfall Runoff ◽  
Global Optimization Methods ◽  
Optimization Search

The calibration of conceptual rainfall runoff (CRR) models is an optimization problem whose objective is to determine the values of the model parameters which provide the best fit between observed and estimated flows. This study investigated the performance of three probabilistic optimization techniques for calibrating the Tank model, a hydrologic model typical of CRR models. These methods were the Shuffled Complex Evolution (SCE), genetic algorithms (GA) and simulated annealing (SA) methods. It was found that performances depended on the choice of the objective function considered and also an the position of the start of the optimization search relative to the global optimum. Of the three global optimization methods (GOM) in the study, the SCE method provided better estimates of the optimal solution than the GA and SA methods. Regarding the efficiency of the GOMs, as expressed by the number of iterations for convergence, the ranking in order of decreasing performance was the SCE, the GA and the SA methods.

Vibration Suppression of the Flexible Joint Manipulator Based on Controllable Local Degrees of Freedom

2011 ◽  
Vol 66-68 ◽  
pp. 989-994
Author(s):  
Zhi Hui Gao ◽  
Jing Jing Yu ◽  
Yu Shu Bian
Keyword(s):  
Vibration Control ◽  
Control Strategy ◽  
Topological Structure ◽  
Degrees Of Freedom ◽  
Vibration Suppression ◽  
Dynamic Performance ◽  
End Effector ◽  
Flexible Joint ◽  
Local Degree ◽  
Flexible Joint Manipulator

In order to suppress vibration of the flexible-joint manipulator, a new topological structure of the manipulator with the controllable local degrees of freedom is suggested. By kinematic and dynamic analysis, it is found that arbitrary motions introduced by the controllable local degrees of freedom are independent of the nominal end-effector motion, but can greatly affect dynamic performance of the manipulator. As a result, a vibration control strategy is put forward based on the controllable local degree of freedom. By planning the branch link motion, the vibration of the flexible-joint manipulator can be reduced. The results of numerical simulations verify the effectiveness of the vibration control strategy proposed in this paper.

A Special Multiobjective Evolutionary Algorithm for Solving Complicated Nonlinear Equations Systems

2014 ◽  
Vol 701-702 ◽  
pp. 18-23
Author(s):  
Chun An Liu
Keyword(s):  
Evolutionary Algorithm ◽  
Nonlinear Equations ◽  
Optimization Problem ◽  
Optimal Solution ◽  
Optimization Methods ◽  
Multi Objective Optimization ◽  
Information Industry ◽  
Multi Objective ◽  
Application Fields ◽  
Industry Network

It is well known that nonlinear equations systems (NESS) is a subclass of nonlinear optimization problem, it exists in many application fields, such as information industry, network design, mechanics and robotics, etc.. How to design feasible and effective optimization methods to obtain the optimal solution or satisfied precision requirement’s optimal solution for complicated NESS is very important in computation fields. In this paper, each nonlinear sub-equation of NESS is approximately regarded as a sub-objective function of multi-objective optimization problem, then the original nonlinear equations systems is transformed into a multi-objective optimization problem, and the equivalence relation of the solution between the original NESS and the transformed multi-objective optimization problem is given. In order to effectively solve the nonlinear equations systems, a self-adaptive levy mutation operation is proposed, and a multi-objective optimization evolutionary algorithm to solve the nonlinear equations systems was designed. Computer simulations demonstrate the proposed algorithm can not only increase the diversity of evolutionary population but also make the evolution population quickly to approach the optimal solution or satisfied precision requirement’s optimal solution.

Optimization of dynamic parameters for a traction-type passenger elevator using a dynamic byte coding genetic algorithm

2008 ◽  
Vol 223 (3) ◽  
pp. 595-605 ◽  
Author(s):  
D Mei ◽  
X Du ◽  
Z Chen
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Dynamic Model ◽  
Optimization Model ◽  
Degrees Of Freedom ◽  
Dynamic Performance ◽  
Optimal Solution ◽  
Dynamic Parameter ◽  
Dynamic Parameters ◽  
Encoding Method

To decrease the vibration and improve the dynamic performance of traction-type passenger elevators, an accurate vertical dynamic model with nine degrees of freedom for a gearless 2: 1 traction-type passenger elevator system is presented. Then, an optimization model of dynamic parameters for this type of passenger elevator is proposed based on the dynamic model. The optimization model takes the amplitude of vibration acceleration response of the elevator cage as the objective function. Various exciting forces and various working conditions can be considered by using corresponding weight coefficients in the objective function. To get higher efficiency and stronger robustness of optimized value, a dynamic byte coding genetic algorithm in solving the optimization model by combining the advantages of binary coding method with dynamic parameter encoding method is proposed, and the optimal solution is verified by sensitivity analysis. A practical engineering optimization for a 2: 1 traction-type passenger elevator system shows that the optimization model and method of dynamic parameters proposed in this article are effective.

scholarly journals A Review of Optimization Algorithms in Solving Hydro Generation Scheduling Problems

Energies ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 2787 ◽  
Author(s):  
Ali Thaeer Hammid ◽  
Omar I. Awad ◽  
Mohd Herwan Sulaiman ◽  
Saraswathy Shamini Gunasekaran ◽  
Salama A. Mostafa ◽  
...  
Keyword(s):  
Power Systems ◽  
Optimal Solution ◽  
Optimization Methods ◽  
Maximum Energy ◽  
Optimization Techniques ◽  
Parameters Optimization ◽  
Ecological Effect ◽  
Scheduling Problems ◽  
Generation Scheduling ◽  
Important Position

The optimal generation scheduling (OGS) of hydropower units holds an important position in electric power systems, which is significantly investigated as a research issue. Hydropower has a slight social and ecological effect when compared with other types of sustainable power source. The target of long-, mid-, and short-term hydro scheduling (LMSTHS) problems is to optimize the power generation schedule of the accessible hydropower units, which generate maximum energy by utilizing the available potential during a specific period. Numerous traditional optimization procedures are first presented for making a solution to the LMSTHS problem. Lately, various optimization approaches, which have been assigned as a procedure based on experiences, have been executed to get the optimal solution of the generation scheduling of hydro systems. This article offers a complete survey of the implementation of various methods to get the OGS of hydro systems by examining the executed methods from various perspectives. Optimal solutions obtained by a collection of meta-heuristic optimization methods for various experience cases are established, and the presented methods are compared according to the case study, limitation of parameters, optimization techniques, and consideration of the main goal. Previous studies are mostly focused on hydro scheduling that is based on a reservoir of hydropower plants. Future study aspects are also considered, which are presented as the key issue surrounding the LMSTHS problem.

A modified firefly algorithm for the inverse kinematics solutions of robotic manipulators

2021 ◽  
Vol 28 (3) ◽  
pp. 257-275
Author(s):  
Jesus Hernandez-Barragan ◽  
Carlos Lopez-Franco ◽  
Nancy Arana-Daniel ◽  
Alma Y. Alanis ◽  
Adriana Lopez-Franco
Keyword(s):  
Inverse Kinematics ◽  
Degrees Of Freedom ◽  
Firefly Algorithm ◽  
Statistical Tests ◽  
Robotic Manipulators ◽  
Optimization Techniques ◽  
Multimodal Optimization ◽  
End Effector ◽  
Prismatic Joints ◽  
Joint Limits

The inverse kinematics of robotic manipulators consists of finding a joint configuration to reach a desired end-effector pose. Since inverse kinematics is a complex non-linear problem with redundant solutions, sophisticated optimization techniques are often required to solve this problem; a possible solution can be found in metaheuristic algorithms. In this work, a modified version of the firefly algorithm for multimodal optimization is proposed to solve the inverse kinematics. This modified version can provide multiple joint configurations leading to the same end-effector pose, improving the classic firefly algorithm performance. Moreover, the proposed approach avoids singularities because it does not require any Jacobian matrix inversion, which is the main problem of conventional approaches. The proposed approach can be implemented in robotic manipulators composed of revolute or prismatic joints of n degrees of freedom considering joint limits constrains. Simulations with different robotic manipulators show the accuracy and robustness of the proposed approach. Additionally, non-parametric statistical tests are included to show that the proposed method has a statistically significant improvement over other multimodal optimization algorithms. Finally, real-time experiments on five degrees of freedom robotic manipulator illustrate the applicability of this approach.

Hybrid Method for Multi-Target Parametric Design

1993 ◽  
Author(s):  
Jami J. Shah ◽  
Jian Wu
Keyword(s):  
Hybrid Method ◽  
Optimization Problem ◽  
Parametric Design ◽  
Design Method ◽  
Mathematical Optimization ◽  
Optimization Methods ◽  
Statistical Technique ◽  
Optimization Techniques ◽  
Quality Requirements ◽  
Optimal Quality

Abstract This paper examines optimization techniques for parametric design based on statistical, mathematical, and heuristic models. A hybrid method is then proposed based on the strengths of several of these approaches. The new method, called multi-target parametric design method, combines Taguchi’s methodology, conventional (mathematical) optimization methods, and MANOVA statistical technique. It can be used to optimize composite utility functions, while satisfying the quality requirements. The method involves three main steps. First, by applying Taguchi’s method, the optimal quality is determined with a certain set of control variables. Second, these variables are transformed into variable constraints through a relaxing process. Finally, the optimization problem is solved for other design targets under these constraints, using conventional mathematical optimization methods or the Taguchi method.

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