Dynamics Modeling and Identification of a Dual-Blade Wafer Handling Robot

2013 ◽  
Author(s):  
Xiaowen Yu ◽  
Cong Wang ◽  
Yu Zhao ◽  
Masayoshi Tomizuka
Keyword(s):  
Dynamic Model ◽  
Coulomb Friction ◽  
Viscous Friction ◽  
Parallel Robot ◽  
Least Square ◽  
Dynamic Parameters ◽  
Dynamics Modeling ◽  
Dynamic Identification ◽  
Least Square Regression ◽  
Reliable Model

This paper presents the dynamics modeling and dynamic identification of a dual-blade wafer handling robot. An explicit form dynamic model for this 8-link parallel robot is proposed. The dynamic model is transformed into a decoupled form to enable dynamic parameters identification with least-square regression. A well conditioned trajectory is chosen for identification experiment. Both viscous friction and Coulomb friction are considered to make the model more reliable. Model has been validated by experiments.

A parameter identification method for robot dynamic models using a balancing mechanism

Robotica ◽  
1989 ◽  
Vol 7 (4) ◽  
pp. 327-337 ◽  
Author(s):  
T. G. Lim ◽  
H. S. Cho ◽  
W. K. Chung
Keyword(s):  
Dynamic Model ◽  
Dynamic Models ◽  
Least Square ◽  
Estimation Accuracy ◽  
Model Parameters ◽  
Robot Dynamics ◽  
Dynamic Parameters ◽  
Joint Torques ◽  
Motion Data ◽  
Identification Method

SUMMARYAccurate modeling of robot dynamics is a prerequisite for the design of model-based control schemes and enhancement of the performance of the robot. The dynamic parameters associated with a pseudo-inertia matrix are often difficult to identify accurately because the inertia torques are small in comparison to gravity loadings, thus creating signal processing problem. The identification method presented in this paper utilizes a balancing mechanism which increases the estimation accuracy of the dynamic parameters. The balancing mechanism has the effect of amplifying the inertia-related torque signal by eliminating gravity loadings acting on the robot joints. A series of motion data were experimentally obtained through sequential test steps. By incorporating the measured information about joint torques, angular positions, velocities and accelerations the least square algorithm was used to identify the dynamic parameters. The estimated values were converted to those of the original robot model to obtain its dynamic model parameters. The identified robot dynamic model was shown to be accurate enough to predict the actual robot motions.

scholarly journals Load Parameter Identification for Parallel Robot Manipulator Based on Extended Kalman Filter

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Shijie Song ◽  
Xiaolin Dai ◽  
Zhangchao Huang ◽  
Dawei Gong
Keyword(s):  
Kalman Filter ◽  
Dynamic Model ◽  
Extended Kalman Filter ◽  
Robot Manipulator ◽  
External Disturbance ◽  
Parallel Robot ◽  
Load Parameter ◽  
Identification Algorithm ◽  
Dynamic Parameters ◽  
Dynamic Coupling

Load is the main external disturbance of a parallel robot manipulator. This disturbance will cause dynamic coupling among different degrees of freedom and make heaps of model-based control methods difficult to apply. In order to compensate this disturbance, it is crucial to obtain an accurate dynamic model of load. However, in practice, the load is always uncertain and its dynamic parameters are arduous to know a priori. To cope with this problem, this paper proposes a novel and simple approach to identify the dynamic parameters of load. Firstly, the dynamic model of the parallel robot manipulator with uncertain load is established and the dynamic coupling caused by load is also analyzed. Then, according to the dynamic model, the excitation signal is designed and a weak nonlinear dynamic model is derived. Furthermore, the identification model is presented and the identification algorithm based on the extended Kalman filter is designed. Lastly, numerical simulation results, obtained using a six-degree-of-freedom Gough–Stewart parallel manipulator, demonstrate the good estimation performance of the proposed method.

scholarly journals Joints dynamic identification and modeling based on FRFs data

2018 ◽  
Vol 189 ◽  
pp. 01010
Author(s):  
Guanhua Dong ◽  
Wei Wu ◽  
Jianhui Zhou
Keyword(s):  
Frequency Response ◽  
Dynamic Model ◽  
Dynamic Properties ◽  
Dynamic Stiffness ◽  
Least Square Method ◽  
Least Square ◽  
Experimental Results ◽  
Response Functions ◽  
Dynamic Identification ◽  
Inconsistent Equation

The problem of joints dynamic identification and modeling is discussed in this paper. The theoretical dynamic model of joints is established by FRFs (frequency response functions) data, and formulas for identifying the joints dynamic properties is deduced. The equivalent value of dynamic stiffness is extracted by solving the inconsistent equation using the least square method. The experimental example is provided to validate the feasibility and accuracy of the proposed method, the predicted result showing good fitting with experimental results.

Dynamic Parameters Identification for Tong & Tong-Carrier of a Forging Manipulator

2011 ◽  
Vol 121-126 ◽  
pp. 2006-2010
Author(s):  
Ning Bo Cheng ◽  
Li Wen Guan ◽  
Li Ping Wang ◽  
Jian Han
Keyword(s):  
Dynamic Model ◽  
Relative Error ◽  
Linear Form ◽  
Least Square Method ◽  
Least Square ◽  
Dynamic Parameters ◽  
Mass Center ◽  
Simulation Results ◽  
Forging Manipulator ◽  
Center Parameter

This paper deals with the dynamic parameters of the combination of the tong, the tong-carrier and (or without) a forging (link TCF). Two linear form equations of the dynamic model of link TCF about the dynamic parameters are obtained. And then based on two linear form equations, the least square method is adopted to identify the parameters. Simulation results show that the identified dynamic parameters, mass m, moment of inertia IL and the mass center parameter b1, have a small relative error that no more than 5%.

Dynamic Parameters of Pultruded GFRP Structures for Seismic Protection of Historical Building Heritage

2014 ◽  
Vol 624 ◽  
pp. 461-469 ◽  
Author(s):  
Giosuè Boscato ◽  
Salvatore Russo
Keyword(s):  
Least Square ◽  
Fiber Reinforced Polymers ◽  
Seismic Protection ◽  
Complex Frequency ◽  
Dynamic Parameters ◽  
Fiber Reinforced ◽  
Dynamic Identification ◽  
Historical Building ◽  
Reinforced Polymers ◽  
Behaviour Factor

The seismic events in the last decades evidenced the vulnerability of the architectural heritage with respect to these phenomena. Therefore, timely provisional and permanent interventions are often required in post-seismic scenarios.In response to the call for more efficacious solutions, a great deal of interest has been given to glass fiber-reinforced polymers (GFRPs) composite. GFRP composites offer the advantage of high strength, low self-weight and durability.This research proposes some first evaluations on the dynamic behaviour of pultruded FRPs (Fiber Reinforced Polymers) strut and tie spatial structure for seismic protection of historical building heritage. The dynamic identification has been carried out using the ambient vibrations test to measure the mode of vibration, frequencies, displacements and damping ratios of the structures. The Operational Modal Analysis (OMA) has been carried out to identify the modal characteristics through poly-reference Least Square Complex Frequency-domain (pLSFC) estimator.Basing on the experimental results the dissipative capacity has been evaluated through the calculation of the behaviour factorq.The experimental dynamic parameters were used to calibrate a numerical finite element model employed under the hypothesis of kinematic equivalence to evaluate theqfactor considering the elastic-brittle behaviour of FRP material. The dissipative capacity of structure was assigned to the global geometric configuration - frame with concentric diagonal bracings - through the strength hierarchy criteria locating the dissipative zones in the tensile diagonals. The analysis was carried out considering some typological variations to investigate the variability of the behaviour factorq.

Ease of Doing Business and Its Impact on Inward FDI

2018 ◽  
Vol 1 (1) ◽  
pp. 52 ◽  
Author(s):  
Mohamed Tareq Hossain ◽  
Zubair Hassan ◽  
Sumaiya Shafiq ◽  
Abdul Basit
Keyword(s):  
Regression Model ◽  
Causal Relationship ◽  
World Bank ◽  
Least Square ◽  
Doing Business ◽  
Least Square Regression ◽  
Foreign Countries ◽  
Ease Of Doing Business ◽  
The Impact ◽  
Starting A Business

This study investigates the impact of Ease of Doing Business on Inward FDI over the period from 2011 to 2015 across the globe. This study measures ease of doing business using starting a business, getting credit, registering property, paying taxes and enforcing contracts. The research used a sample of 177 countries from 190 countries listed in World Bank. Least square regression model via E-views software used to examine causal relationship. The study found that ease of doing business indicators ‘Enforcing Contracts’ was found to have a positive significant impact on Inward FDI. Nevertheless, ‘Getting Credit’ and ‘Registering Property’ were found to have a negative significant impact on Inward FDI. However, ‘Starting a Business’ and ‘Paying Taxes’ have no significant impact on Inward FDI in the studied timeframe of this research. The findings of the study suggested the ease of doing business enables inward FDI through better contract enforcements, getting credit and registering property. The findings of the research will assist international managers and companies to know the importance of ease of doing business when investing in foreign countries through FDI.

Modeling CO2 exchange and meteorological factors of an apple orchard using partial least square regression

2020 ◽  
Vol 27 (35) ◽  
pp. 43439-43451 ◽  
Author(s):  
Jianfeng Yang ◽  
Yumin Duan ◽  
Xiaoni Yang ◽  
Mukesh Kumar Awasthi ◽  
Huike Li ◽  
...  
Keyword(s):  
Meteorological Factors ◽  
Co2 Exchange ◽  
Apple Orchard ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Least Square Regression

Lower limb exoskeleton robots’ dynamics parameters identification based on improved beetle swarm optimization algorithm

Robotica ◽  
2022 ◽  
pp. 1-16
Author(s):  
Peng Zhang ◽  
Junxia Zhang
Keyword(s):  
Optimization Algorithm ◽  
Robot Control ◽  
Search Algorithm ◽  
Optimal Solution ◽  
Global Optimum ◽  
Identification Accuracy ◽  
Dynamic Parameters ◽  
Dynamics Modeling ◽  
Swarm Optimization ◽  
Exoskeleton Robot

Abstract Efficient and high-precision identification of dynamic parameters is the basis of model-based robot control. Firstly, this paper designed the structure and control system of the developed lower extremity exoskeleton robot. The dynamics modeling of the exoskeleton robot is performed. The minimum parameter set of the identified parameters is determined. The dynamic model is linearized based on the parallel axis theory. Based on the beetle antennae search algorithm (BAS) and particle swarm optimization (PSO), the beetle swarm optimization algorithm (BSO) was designed and applied to the identification of dynamic parameters. The update rule of each particle originates from BAS, and there is an individual’s judgment on the environment space in each iteration. This method does not rely on the historical best solution in the PSO and the current global optimal solution of the individual particle, thereby reducing the number of iterations and improving the search speed and accuracy. Four groups of test functions with different characteristics were used to verify the performance of the proposed algorithm. Experimental results show that the BSO algorithm has a good balance between exploration and exploitation capabilities to promote the beetle to move to the global optimum. Besides, the test was carried out on the exoskeleton dynamics model. This method can obtain independent dynamic parameters and achieve ideal identification accuracy. The prediction result of torque based on the identification method is in good agreement with the ideal torque of the robot control.

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