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Positioning Accuracy Improvement of Industrial Robots Considering Configuration and Payload Effects Via a Hybrid Calibration Approach

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IEEE ACCESS 2020年 8卷 228992-229005页

作者： Hsiao, Jen-Chung Shivam, Kumar Lu, I-Fang Kam, Tai-Yan Precis Machinery Res & Dev Ctr PMC Taichung 40768 Taiwan Natl Chiao Tung Univ Dept Mech Engn Hsinchu 30010 Taiwan

Robot calibration of an industrial robot is of importance for those applications requiring high positioning accuracy. The use of numerical optimization techniques to identify the accurate kinematic parameters and tackle the residual errors for improving positioning accuracy is still challenging. The difficulties in using the conventional optimization techniques is associated with the expensive computation of the second derivative terms in the Hessian matrix and even more linked to the additional improvement of the residual errors induced by the configuration and payload effects for the practical applications. A hybrid calibration procedure, which is robust and efficient, is proposed to handle the said problems in this study. The first step is to utilize the Broyden-Fletcher-Goldfarb-Shanno (bfgs) algorithm together with the quasi-Newton method to optimize the cost function with non-smooth nature established using massive measurement data. In the second step, two kinds of artificial neural network (ANN) algorithms are employed to further improve the nonlinear residual errors induced by payload and configuration effects. After the completion of the hybrid calibration, improvements of 88.1% and 80.1% have been attained, respectively, for the mean and maximum positioning errors of the robot end-effector, i.e., the mean/maximum positioning errors are reduced from 2.613mm/6.294mm to 0.310mm/1.255mm for 840 untrained measurement data. The experimental results also validated the effectiveness of the proposed method.

关键词： Robots Service robots Calibration Kinematics Artificial neural networks Position measurement Payloads Artificial neural network bfgs algorithm industrial robots robot calibration

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Three-dimensional phase-field modeling of mode I plus II/III failure in solids

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COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING 2021年 373卷 113537-113537页

作者： Wu, Jian-Ying Huang, Yuli Zhou, Hao Nguyen, Vinh Phu South China Univ Technol State Key Lab Subtrop Bldg Sci Guangzhou 510641 Peoples R China South China Univ Technol Dept Civil Engn Guangzhou 510641 Peoples R China Arup 560 Mission StSuite 700 San Francisco CA 94105 USA Monash Univ Dept Civil Engn Clayton Vic 3800 Australia

One major merit of phase-field models for fracture is that cracks nucleation, propagation, branching, merging, coalescence and even fragmentation, etc., can be accounted for seamlessly within a standalone regularized variational framework. This fascinating feature overcomes the cumbersomeness in the characterization of non-smooth crack surfaces and the tracking of complex crack paths. However, the numerical algorithms frequently adopted in solving the coupled governing equations are not robust or efficient enough, together with the high computational cost in resolving the fracture process zone, largely hindering application of these models to general 3D problems. In this work, several 3D benchmark problems involving mode I, I+II or I+III failure in brittle and quasi-brittle solids is addressed based on our recent theoretical and numerical progresses on the unified phase-field theory for damage and fracture (Wu, 2017). Complex 3D fracture problems with over 2 million elements and more than 6 million degrees of freedom (dofs) can be tackled using normal computation facilities within acceptable computational time. Moreover, we are able to not only reproduce qualitatively evolution of the complex fracture pattern, but also compare quantitatively the global responses against experimental results. With the need neither to characterize the non-smooth crack surface nor to track the twisting crack path, the 3D computer implementation is almost the same as the 2D counterpart, paving the way to the phase-field modeling of large scale engineering problems. (C) 2020 Elsevier B.V. All rights reserved.

关键词： Phase-field theory Damage Fracture Localized failure bfgs algorithm

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NEUROCOMPUTING 2024年 607卷

作者： Xue, Cuiping Zhang, Tie Xiao, Dong Northeastern Univ Coll Sci 3-11 Wenhua Rd Shenyang 110819 Liaoning Peoples R China Northeastern Univ Coll Informat Sci & Engn Shenyang 110819 Peoples R China Northeastern Univ Liaoning Key Lab Intelligent Diag & Safety Met Ind Shenyang 110819 Peoples R China

In recent years, some progress has been made in fault diagnosis of multi-block regression model, but multi-block method uses the relationship between variables in Hilbert space to block, while the relationship between variables in complex industrial systems often exists in Banach space. In addition, Bayesian fusion method is used in fault monitoring, which can not accurately process the sub-block information and judge whether the fault information is related to the output. In this paper, a new multi-block method is proposed. Firstly, this method uses Ball Covariance (BCov) suitable for Banach space to describe the correlation between variables, and combines Kmeans clustering method to block variables to ensure that the blocking method is more reasonable. Secondly, an improved orthogonal decomposition Broyden-Fletcher -Goldfarb-Shanno (bfgs) algorithm is proposed. The MObfgs algorithm performs orthogonal projection on potential structures, removing information orthogonal to the output from the input block. Furthermore, through complete orthogonal decomposition between the input block and the output block, information related to and unrelated to the output is completely separated, and used to detect output related and unrelated faults, respectively. Thirdly, at the block level, MObfgs algorithm is used for fault detection and contribution graph method for fault diagnosis. Finally, numerical examples and Tennessee Eastman (TE) process simulation verify the effectiveness of this method.

关键词： bfgs algorithm Ball covariance Multi block Output related and unrelated fault diagnosis Tennessee Eastman process

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Hybrid Invasive Weed Optimization algorithm for Parameter Inversion Problems

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INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE 2018年第9期32卷

作者： Deng, Tan Du, Jiayi Hunan Univ Coll Informat Sci & Engn Changsha 410082 Hunan Peoples R China Cent South Univ Forestry & Technol Coll Comp & Informat Engn Changsha 410004 Hunan Peoples R China

A hybrid invasive weed optimization (HIWO) algorithm based on the Broyden-Fletcher-Goldfarb-Shanno (bfgs) algorithm is proposed for the problems on parameter inversion of the nonlinear models of sun shadow with integer variables in the study. Our presented algorithm can take full advantage of the local search ability of bfgs algorithm and the global search ability of invasive weed optimization (IWO) algorithm. The HIWO algorithm can not only reverse the date of sun shadow model successfully, but also conquer the weaknesses that the classic mathematical methods are hard to address integer nonlinear optimization problems by utilizing integers in some random variables from algorithms. The results of numerical experiments demonstrate that the HIWO algorithm has not only high computing accuracy, but also fast convergence speed. It can effectively improve the accuracy and efficiency of the techniques of sun shadow location, and afford an effective and efficient technique to handle the issues of integer parameter inversion in engineering applications.

关键词： bfgs algorithm hybrid algorithm invasive weed optimization parameter inversion solar shadow

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Fast individual ancestry inference from DNA sequence data leveraging allele frequencies for multiple populations

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BMC BIOINFORMATICS 2015年第1期16卷 4-4页

作者： Bansal, Vikas Libiger, Ondrej Univ Calif San Diego Dept Pediat La Jolla CA 92093 USA Scripps Translat Sci Inst La Jolla CA 92037 USA

Background: Estimation of individual ancestry from genetic data is useful for the analysis of disease association studies, understanding human population history and interpreting personal genomic variation. New, computationally efficient methods are needed for ancestry inference that can effectively utilize existing information about allele frequencies associated with different human populations and can work directly with DNA sequence reads. Results: We describe a fast method for estimating the relative contribution of known reference populations to an individual's genetic ancestry. Our method utilizes allele frequencies from the reference populations and individual genotype or sequence data to obtain a maximum likelihood estimate of the global admixture proportions using the bfgs optimization algorithm. It accounts for the uncertainty in genotypes present in sequence data by using genotype likelihoods and does not require individual genotype data from external reference panels. Simulation studies and application of the method to real datasets demonstrate that our method is significantly times faster than previous methods and has comparable accuracy. Using data from the 1000 Genomes project, we show that estimates of the genome-wide average ancestry for admixed individuals are consistent between exome sequence data and whole-genome low-coverage sequence data. Finally, we demonstrate that our method can be used to estimate admixture proportions using pooled sequence data making it a valuable tool for controlling for population stratification in sequencing based association studies that utilize DNA pooling. Conclusions: Our method is an efficient and versatile tool for estimating ancestry from DNA sequence data and is available from https://***/site/vibansal/software/iAdmix.

关键词： Admixture estimation High-throughput sequencing Allele frequencies Maximum likelihood Ancestry bfgs algorithm

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Prediction of Flow Duration Curves for Ungauged Basins with Quasi-Newton Method

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Journal of Water Resource and Protection 2013年第1期5卷 97-110页

作者： Mutlu Yasar Neset Orhan Baykan Department of Civil Engineering Pamukkale UniversityDenizliTurkey

Prediction of flow-duration-curves (FDC) is an important task for water resources planning, management and hydraulic energy production. Classification of the basins as carstic and non-carstic may be used to estimate parameters of the FDC with predictive tools for catchments with/without observed stream flow. There is a need for obtaining FDC for ungauged stations for efficient water resource planning. Thus, study proposes a quite new approach, called the EREFDC model, for estimating the parameters of the FDC for which the parameters of the FDC are obtained with quasi-Newton method. Estimation are made for using the bv gauged stations at first than the FDC parameters are estimated for ungauged stations based on drainage area, annual mean precipitation, mean permeability, mean slope, latitude, longitude, and elevation from the mean sea level are used. The EREFDC model consists of various type of linear- and nonlinear mathematical equations, is able to predict a wide range of the FDC parameters for gauged and ungauged basins. The method is applied to 72 unimpaired catchments studied are about for 50 years average daily measured stream flow. Results showed that the EREFDC model may be used for estimating. FDC parameters for ungauged hydrological basins in order to find FDC for ungauged stations. Results also showed that the EREFDC model performs better in carstic regions than non-carstic regions. In addition, parameters of FDC for tributaries at the basins with insufficient flow data or without flow data may be determined by using basin characteristics.

关键词： Flow Duration Curve Optimization bfgs algorithm Basin Characteristics

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Solution of the maximum distillate on a batch distillation column by a Pseudo-Newton method

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RESULTS IN ENGINEERING 2023年 19卷

作者： Rodriguez-Robles, Christian Felipe Hernandez-Escoto, Hector Hernandez, Salvador Univ Guanajuato Dept Ingn Quim Noria Alta S-N Guanajuato 36050 Gto Mexico

This paper presents a new algorithm for the solution of the maximum distillate problem based on Pontryagin's maximum principle. Four cases of study were analyzed with the algorithm. The first case is a literature problem where the column uses twenty trays to distillate ten components, the second case is a binary mixture with no ideal behavior, the third case is a quaternary mixture, and the last case is a reactive mixture. In all cases, the desired purity was settled as a final constraint. The solution algorithm found the optimal control faster than results reported in literature concerning the CPU time. The batch distillation process is modeled by using a rigorous model with no constant volatility. The proposed algorithm uses the Hamiltonian function to reformulate the maximum distillate problem. Then, the optimal control is solved by a Broyden-Fletcher-Goldfarb-Shanno algorithm. The solution procedure of the indirect approach required the forward integration of the states, the integration of the co-state equations backward in time, and the control input is the distillate flow rate which is parameterized. The binary batch distillation column uses six stages, and the maximum recovery is 95% of the light component with a 95% mol percent on the accumulator. The multicomponent batch distillation column uses 17 stages, and the recovery of the lightest component in the product is 90% mol percent. The reactive case reached 80% conversion.

关键词： Maximum distillate Optimal control Pontryagin's minimum principle bfgs algorithm Batch distillation Reactive distillation

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Application of bfgs-BP in Tunnel Deformation Monitoring Data Processing

Application of BFGS-BP in Tunnel Deformation Monitoring Data...

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2011 International Conference on Internet Computing and Information Services （ICICIS 2011）

作者： WANG Zegen GAO Yuyun HU Guangqiang School of Civil Engineering & Architecture Southwest Petroleum University SWPU School of Oil&Gas Well Engineering Southwest Petroleum University SWPU

In order to overcome the disadvantages such as low calculation precision and convergence rate of traditional BP neural network algorithm, a kind of nonlinear optimization method-bfgs method for unconstrained extreme problem is introduced into BP neural network algorithm, and a bfgs-BP neural network model is developed, which is applied well in tunnel deformation monitoring data processing and forecasting with uncertainty and nonlinearity. With the example of the observation data of vault crown settlement of some tunnel construction process, the test of training and forecast experiments of bfgs- BP were developed. The result shows that bfgs-BP model has higher calculation precision and convergence rate than the traditional one.

关键词： BP neural network bfgs algorithm deformation monitoring data processing

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Application of bfgs-BP in Tunnel Deformation Monitoring Data Processing

Application of BFGS-BP in Tunnel Deformation Monitoring Data...

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2010 4th International Conference on Intelligent Information Technology Application (IITA2010)

作者： WANG Zegen, GAO Yuyun School of Civil Engineering & Architecture Southwest Petroleum University, SWPU Chengdu, China HU Guangqiang School of Oil&Gas Well Engineering Southwest Petroleum University, SWPU Chengdu, China

In order to overcome the disadvantages such as low calculation precision and convergence rate of traditional BP neural network algorithm, a kind of nonlinear optimization method-bfgs method for unconstrained extreme problem is introduced into BP neural network algorithm, and a bfgs-BP neural network model is developed, which is applied well in tunnel deformation monitoring data processing and forecasting with uncertainty and nonlinearity. With the example of the observation data of vault crown settlement of some tunnel construction process, the test of training and forecast experiments of bfgs - BP were developed. The result shows that bfgs-BP model has higher calculation precision and convergence rate than the traditional one.

关键词： BP neural network bfgs algorithm deformation monitoring data processing

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