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11 – 20 of over 1000
Article
Publication date: 18 January 2024

Zaihua Luo, Juliang Xiao, Sijiang Liu, Mingli Wang, Wei Zhao and Haitao Liu

This paper aims to propose a dynamic parameter identification method based on sensitivity analysis for the 5-degree of freedom (DOF) hybrid robots, to solve the problems of too…

Abstract

Purpose

This paper aims to propose a dynamic parameter identification method based on sensitivity analysis for the 5-degree of freedom (DOF) hybrid robots, to solve the problems of too many identification parameters, complex model, difficult convergence of optimization algorithms and easy-to-fall into a locally optimal solution, and improve the efficiency and accuracy of dynamic parameter identification.

Design/methodology/approach

First, the dynamic parameter identification model of the 5-DOF hybrid robot was established based on the principle of virtual work. Then, the sensitivity of the parameters to be identified is analyzed by Sobol’s sensitivity method and verified by simulation. Finally, an identification strategy based on sensitivity analysis was designed, experiments were carried out on the real robot and the results were verified.

Findings

Compared with the traditional full-parameter identification method, the dynamic parameter identification method based on sensitivity analysis proposed in this paper converges faster when optimized using the genetic algorithm, and the identified dynamic model has higher prediction accuracy for joint drive forces and torques than the full-parameter identification models.

Originality/value

This work analyzes the sensitivity of the parameters to be identified in the dynamic parameter identification model for the first time. Then a parameter identification method is proposed based on the results of the sensitivity analysis, which can effectively reduce the parameters to be identified, simplify the identification model, accelerate the convergence of the optimization algorithm and improve the prediction accuracy of the identified model for the joint driving forces and torques.

Details

Industrial Robot: the international journal of robotics research and application, vol. 51 no. 2
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 7 October 2013

M. Vaz Jr, E.L. Cardoso and J. Stahlschmidt

Parameter identification is a technique which aims at determining material or other process parameters based on a combination of experimental and numerical techniques. In recent…

Abstract

Purpose

Parameter identification is a technique which aims at determining material or other process parameters based on a combination of experimental and numerical techniques. In recent years, heuristic approaches, such as genetic algorithms (GAs), have been proposed as possible alternatives to classical identification procedures. The present work shows that particle swarm optimization (PSO), as an example of such methods, is also appropriate to identification of inelastic parameters. The paper aims to discuss these issues.

Design/methodology/approach

PSO is a class of swarm intelligence algorithms which attempts to reproduce the social behaviour of a generic population. In parameter identification, each individual particle is associated to hyper-coordinates in the search space, corresponding to a set of material parameters, upon which velocity operators with random components are applied, leading the particles to cluster together at convergence.

Findings

PSO has proved to be a viable alternative to identification of inelastic parameters owing to its robustness (achieving the global minimum with high tolerance for variations of the population size and control parameters), and, contrasting to GAs, higher convergence rate and small number of control variables.

Originality/value

PSO has been mostly applied to electrical and industrial engineering. This paper extends the field of application of the method to identification of inelastic material parameters.

Details

Engineering Computations, vol. 30 no. 7
Type: Research Article
ISSN: 0264-4401

Keywords

Article
Publication date: 5 January 2010

Mario Pacas, Sebastian Villwock, Piotr Szczupak and Henning Zoubek

The purpose of this paper is to summarize several identification methods for the automatic commissioning of electrical drives that are presented in different earlier papers of the…

Abstract

Purpose

The purpose of this paper is to summarize several identification methods for the automatic commissioning of electrical drives that are presented in different earlier papers of the same authors. This paper is intended as a contribution to the development of expert systems, taking into account parametric models of the mechanical and electrical subsystem as well as the corresponding parameter fitting.

Design/methodology/approach

Some system parameters, which are mandatory for the commissioning of electrical and mechanical systems are often not known. For their identification, a method based on the frequency response calculation utilizing the Welch method is now presented. The main focus of the work is directed to the measurement of the frequency response by exciting the system with pseudo‐random binary signals and to the subsequent procedure for the calculation of the corresponding parameter by utilizing the Levenberg‐Marquardt algorithm.

Findings

The presented identification procedure leads to outstanding results during the commissioning of the system as well as under normal operation conditions. The identification of the parameter of the mechanical and electrical systems is therefore possible during the commissioning of the drive as well as in running machines. Further, some restrictions regarding the measurement facilities are presented.

Originality/value

The presented identification procedure can be applied in a variety of conditions and can be applied for diagnostic tasks. New measurement and considerations regarding the restrictions of the applied method also under normal operation of the systems underline this fact.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 29 no. 1
Type: Research Article
ISSN: 0332-1649

Keywords

Article
Publication date: 2 January 2018

Yong Xie, Pan Liu and Guoping Cai

The purpose of this paper is to present an on-orbit frequency identification method for spacecraft directly using attitude maneuver data. Natural frequency of flexible solar…

Abstract

Purpose

The purpose of this paper is to present an on-orbit frequency identification method for spacecraft directly using attitude maneuver data. Natural frequency of flexible solar arrays plays an important role in attitude control design of spacecraft with solar arrays, and its precision will directly affect the accuracy of attitude maneuver. However, when the flexibility of the solar arrays is large, because of air damping, gravity effect etc., the frequency obtained by ground test shows great error compared with the on-orbit real value. One solution to this problem is to conduct on-orbit identification during which proper identification methods are used to obtain the parameters of interest based on the real on-orbit data of spacecraft.

Design/methodology/approach

The observer/Kalman filter identification and eigensystem realization algorithm are used as identification methods, and the attitude maneuver controller is designed using the rigid-body dynamics method.

Findings

Two conclusions are drawn in this paper according to results of numerical simulations. The first one is that the attitude controller based on the rigid-body dynamics method is effective in attitude maneuver of the spacecraft. The second one is that the on-orbit parameter identification can be directly achieved by using attitude maneuver data of spacecraft without adding additional missions.

Practical implications

Based on the methods proposed in this paper, it is convenient to obtain the natural frequencies of the spacecraft using the data of the attitude maneuver, which may greatly reduce the cost of on-orbit identification test.

Originality/value

The way of obtaining natural frequencies based on attitude maneuver data of spacecraft provides high originality and value for practical application.

Details

Aircraft Engineering and Aerospace Technology, vol. 90 no. 1
Type: Research Article
ISSN: 1748-8842

Keywords

Article
Publication date: 18 April 2023

R. Anish and K. Shankar

The purpose of this paper is to apply the novel instantaneous power flow balance (IPFB)-based identification strategy to a specific practical situation like nonlinear lap joints…

Abstract

Purpose

The purpose of this paper is to apply the novel instantaneous power flow balance (IPFB)-based identification strategy to a specific practical situation like nonlinear lap joints having single and double bolts. The paper also investigates the identification performance of the proposed power flow method over conventional acceleration-matching (AM) methods and other methods in the literature for nonlinear identification.

Design/methodology/approach

A parametric model of the joint assembly formulated using generic beam element is used for numerically simulating the experimental response under sinusoidal excitations. The proposed method uses the concept of substructure IPFB criteria, whereby the algebraic sum of power flow components within a substructure is equal to zero, for the formulation of an objective function. The joint parameter identification problem was treated as an inverse formulation by minimizing the objective function using the Particle Swarm Optimization (PSO) algorithm, with the unknown parameters as the optimization variables.

Findings

The errors associated with identified numerical results through the instantaneous power flow approach have been compared with the conventional AM method using the same model and are found to be more accurate. The outcome of the proposed method is also compared with other nonlinear time-domain structural identification (SI) methods from the literature to show the acceptability of the results.

Originality/value

In this paper, the concept of IPFB-based identification method was extended to a more specific practical application of nonlinear joints which is not reported in the literature. Identification studies were carried out for both single-bolted and double-bolted lap joints with noise-free and noise-contamination cases. In the current study, only the zone of interest (substructure) needs to be modelled, thus reducing computational complexity, and only interface sensors are required in this method. If the force application point is outside the substructure, there is no need to measure the forcing response also.

Article
Publication date: 21 July 2020

Guanghui Liu, Qiang Li, Lijin Fang, Bing Han and Hualiang Zhang

The purpose of this paper is to propose a new joint friction model, which can accurately model the real friction, especially in cases with sudden changes in the motion direction…

Abstract

Purpose

The purpose of this paper is to propose a new joint friction model, which can accurately model the real friction, especially in cases with sudden changes in the motion direction. The identification and sensor-less control algorithm are investigated to verify the validity of this model.

Design/methodology/approach

The proposed friction model is nonlinear and it considers the angular displacement and angular velocity of the joint as a secondary compensation for identification. In the present study, the authors design a pipeline – including a manually designed excitation trajectory, a weighted least squares algorithm for identifying the dynamic parameters and a hand guiding controller for the arm’s direct teaching.

Findings

Compared with the conventional joint friction model, the proposed method can effectively predict friction factors during the dynamic motion of the arm. Then friction parameters are quantitatively obtained and compared with the proposed friction model and the conventional friction model indirectly. It is found that the average root mean square error of predicted six joints in the proposed method decreases by more than 54%. The arm’s force control with the full torque using the estimated dynamic parameters is qualitatively studied. It is concluded that a light-weight industrial robot can be dragged smoothly by the hand guiding.

Practical implications

In the present study, a systematic pipeline is proposed for identifying and controlling an industrial arm. The whole procedure has been verified in a commercial six DOF industrial arm. Based on the conducted experiment, it is found that the proposed approach is more accurate in comparison with conventional methods. A hand-guiding demo also illustrates that the proposed approach can provide the industrial arm with the full torque compensation. This essential functionality is widely required in many industrial arms such as kinaesthetic teaching.

Originality/value

First, a new friction model is proposed. Based on this model, identifying the dynamic parameter is carried out to obtain a set of model parameters of an industrial arm. Finally, a smooth hand guiding control is demonstrated based on the proposed dynamic model.

Details

Industrial Robot: the international journal of robotics research and application, vol. 47 no. 6
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 10 June 2022

Chao Tan, Huan Zhao and Han Ding

Branched articulated robots (BARs) are highly non-linear systems; accurate dynamic identification is critical for model-based control in high-speed and heavy-load applications…

Abstract

Purpose

Branched articulated robots (BARs) are highly non-linear systems; accurate dynamic identification is critical for model-based control in high-speed and heavy-load applications. However, due to some dynamic parameters being redundant, dynamic models are singular, which increases the calculation amount and reduces the robustness of identification. This paper aims to propose a novel methodology for the dynamic analysis and redundant parameters elimination of BARs.

Design/methodology/approach

At first, the motion of a rigid body is divided into constraint-dependent and constraint-independent. The redundancy of inertial parameters is analyzed from physical constraints. Then, the redundant parameters are eliminated by mapping posterior links to their antecedents, which can be applied for re-deriving the Newton–Euler formulas. Finally, through parameter transformation, the presented dynamic model is non-singular and available for identification directly.

Findings

New formulas for redundant parameters elimination are explicit and computationally efficient. This unifies the redundant parameters elimination of prismatic and revolute joints for BARs, and it is also applicable to other types of joints containing constraints. The proposed approach is conducive to facilitating the modelling phase during the robot identification. Simulation studies are conducted to illustrate the effectiveness of the proposed redundant parameters elimination and non-singular dynamic model determination. Experimental studies are carried out to verify the result of the identification algorithm.

Originality/value

This work proposes to determine and directly identify the non-redundant dynamic model of robots, which can help to reduce the procedure of obtaining the reversible regression matrix for identification.

Details

Industrial Robot: the international journal of robotics research and application, vol. 49 no. 6
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 3 July 2009

Wissam Karam and Jean‐Charles Mare

The purpose of this paper is to develop accurate model and simulation of mechanical power transmission within roller‐screw electromechanical actuators with special attention to…

1741

Abstract

Purpose

The purpose of this paper is to develop accurate model and simulation of mechanical power transmission within roller‐screw electromechanical actuators with special attention to friction, compliance and inertia effects. Also, to propose non‐intrusive experiments for the identification of model parameters with an integrator or system‐oriented view.

Design/methodology/approach

At system design level, the actuation models need to reproduce with confidence the energy losses and the main dynamic effects. The adopted modelling methodology is based on non‐intrusive measurements taken on a standard actuator test‐bench. The actuator model is first structured with respect to the bond‐graph formalism that allows a clear identification of the considered effects and associated causalities for model implementation. Various approaches are then combined, mixing blocked or moving load, position or torque control and time or frequency domains analysis. The friction representation model is suggested using a step‐by‐step approach that covers a wide domain of operation. The model is validated under varying torque and speed conditions.

Findings

A structured model is introduced with support of the bond‐graph formalism. Combining blocked/moving load and time/frequency domain experiments allows the development of progressive model identification. An advanced friction representation model is proposed including the effects of speed, transmitted force, quadrant of operation and roller‐screw preload.

Originality/value

Mechanical transmission energy losses and dynamics are modelled in a system‐oriented view without massive need to confidential design parameters. Not only speed but also load and operation quadrant effects are reproduced by the proposed friction model. The non‐intrusive experimental procedure is made consistent with use of a standard actuator test‐bench.

Details

Aircraft Engineering and Aerospace Technology, vol. 81 no. 4
Type: Research Article
ISSN: 0002-2667

Keywords

Article
Publication date: 22 March 2013

Fan Yang, Zongji Chen and Chen Wei

The purpose of this paper is to build nonlinear model of a small rotorcraft‐based unmanned aerial vehicles (RUAV), using nonlinear system identification method to estimate the…

Abstract

Purpose

The purpose of this paper is to build nonlinear model of a small rotorcraft‐based unmanned aerial vehicles (RUAV), using nonlinear system identification method to estimate the parameters of the model. The nonlinear model will be used in robust control system design and aerodynamic analysis.

Design/methodology/approach

The nonlinear model is built based on mechanism theory, aerodynamics and mechanics, which can reflect most dynamics in large flight envelop. Genetic algorithm (GA) and time domain flight data is adopted to estimate unknown parameters of the model. The flight data were collected from a series of fight tests. The identification results were also analyzed and validated.

Findings

The nonlinear model of RUAV has better accuracy, the parameters are physical quantities, and having distinctly recognizable values. The GA is suitable for nonlinear system identification. And the results proved the identified model can reflect the dynamic characteristics in extensive area of flight envelop.

Research limitations/implications

The GA requires much more computing power, to identify 12 unknown parameters with 30 iterations, will takes more than 18 hours of a four cores desktop computer. Because of this is an off‐line identification process, and has more accuracy, extra time is acceptable.

Originality/value

GA method has significantly increased the accuracy of the model. The previous work of system identification used a ten states linear model, and using PEM identified 23 coefficients. By carefully building the nonlinear model, it has only 21 unknown parameters, but if the model is linearized, it will get a linear model more than 35 states, which shows nonlinear model contain more dynamics than linear model.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 6 no. 1
Type: Research Article
ISSN: 1756-378X

Keywords

Article
Publication date: 13 December 2017

Shuizhong Zou, Bo Pan, Yili Fu and Shuixiang Guo

The purpose of this paper is to propose a control algorithm to improve the backdrivability performance of minimally invasive surgical robotic arms, so that precise manual…

Abstract

Purpose

The purpose of this paper is to propose a control algorithm to improve the backdrivability performance of minimally invasive surgical robotic arms, so that precise manual manipulations of robotic arms can be performed in the preoperative operation.

Design/methodology/approach

First, the flexible-joint dynamic model of the 3-degree of freedom remote center motion (RCM) mechanisms of minimally invasive surgery (MIS) robot is derived and its dynamic parameters and friction parameters are identified. Next, the angular velocities and angular accelerations of joints are estimated in real time by the designed Kalman filter. Finally, a control algorithm based on Kalman filter is proposed to enhance the backdrivability of RCM mechanisms by compensating for the internally generated gravitational, frictional and inertial resistances experienced during the positioning and orientating.

Findings

The parameter identification for RCM mechanisms can be experimentally evaluated from comparison between the measured torques and the reconstructed torques. The accuracy and convergence of the real-time estimation of angular velocity and acceleration of the joint by the designed Kalman filter can be verified from corresponding simulation experiments. Manual adjustment experiments and animal experiments validate the effectiveness of the proposed backdrivability control algorithm.

Research limitations/implications

The backdrivability control algorithm presented in this paper is a universal method to enhance the manual operation performance of robots, which can be used not only in the medical robot preoperative manual manipulation but also in robot haptic interaction, industrial robot direct teaching and active rehabilitation training of rehabilitation robot and so on.

Originality/value

Compared with other backdrivability design methods, the proposed algorithm achieves good backdrivability for RCM mechanisms without using force sensors and accelerometers. In addition, this paper presents a new static friction compensation approach for a joint moving with very low velocity.

Details

Industrial Robot: An International Journal, vol. 45 no. 1
Type: Research Article
ISSN: 0143-991X

Keywords

11 – 20 of over 1000