A Lagrangian network for kinematic control of redundant robot manipulators
matlab工具箱安装教程
1.1 如果是Matlab安装光盘上的工具箱，重新执行安装程序，选中即可；1.2 如果是单独下载的工具箱，一般情况下仅需要把新的工具箱解压到某个目录。
2 在matlab的file下面的set path把它加上。
3 把路径加进去后在file→Preferences→General的Toolbox Path Caching里点击update Toolbox Path Cache更新一下。
4 用which newtoolbox_command.m来检验是否可以访问。
如果能够显示新设置的路径，则表明该工具箱可以使用了。
把你的工具箱文件夹放到安装目录中“toolbox”文件夹中，然后单击“file”菜单中的“setpath”命令，打开“setpath”对话框，单击左边的“ADDFolder”命令，然后选择你的那个文件夹，最后单击“SAVE”命令就OK了。
MATLAB Toolboxes＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝/zsmcode.htmlBinaural-modeling software for MATLAB/Windows/home/Michael_Akeroyd/download2.htmlStatistical Parametric Mapping (SPM)/spm/ext/BOOTSTRAP MATLAB TOOLBOX.au/downloads/bootstrap_toolbox.htmlThe DSS package for MATLABDSS Matlab package contains algorithms for performing linear, deflation and symmetric DSS. http://www.cis.hut.fi/projects/dss/package/Psychtoolbox/download.htmlMultisurface Method Tree with MATLAB/~olvi/uwmp/msmt.htmlA Matlab Toolbox for every single topic !/~baum/toolboxes.htmleg. BrainStorm - MEG and EEG data visualization and processingCLAWPACK is a software package designed to compute numerical solutions to hyperbolic partial differential equations using a wave propagation approach/~claw/DIPimage - Image Processing ToolboxPRTools - Pattern Recognition Toolbox (+ Neural Networks)NetLab - Neural Network ToolboxFSTB - Fuzzy Systems ToolboxFusetool - Image Fusion Toolboxhttp://www.metapix.de/toolbox.htmWAVEKIT - Wavelet ToolboxGat - Genetic Algorithm ToolboxTSTOOL is a MATLAB software package for nonlinear time series analysis.TSTOOL can be used for computing: Time-delay reconstruction, Lyapunov exponents, Fractal dimensions, Mutual information, Surrogate data tests, Nearest neighbor statistics, Return times, Poincare sections, Nonlinear predictionhttp://www.physik3.gwdg.de/tstool/MATLAB / Data description toolboxA Matlab toolbox for data description, outlier and novelty detectionMarch 26, 2004 - D.M.J. Taxhttp://www-ict.ewi.tudelft.nl/~davidt/dd_tools/dd_manual.htmlMBEhttp://www.pmarneffei.hku.hk/mbetoolbox/Betabolic network toolbox for Matlabhttp://www.molgen.mpg.de/~lieberme/pages/network_matlab.htmlPharmacokinetics toolbox for Matlabhttp://page.inf.fu-berlin.de/~lieber/seiten/pbpk_toolbox.htmlThe SpiderThe spider is intended to be a complete object orientated environment for machine learning in Matlab. Aside from easy use of base learning algorithms, algorithms can be plugged together and can be compared with, e.g model selection, statistical tests and visual plots. This gives all the power of objects (reusability, plug together, share code) but also all the power of Matlab for machine learning research.http://www.kyb.tuebingen.mpg.de/bs/people/spider/index.htmlSchwarz-Christoffel Toolbox/matlabcentral/fileexchange/loadFile.do?objectId=1316&objectT ype=file#XML Toolbox/matlabcentral/fileexchange/loadFile.do?objectId=4278&object Type=fileFIR/TDNN Toolbox for MATLABBeta version of a toolbox for FIR (Finite Impulse Response) and TD (Time Delay) NeuralNetworks./interval-comp/dagstuhl.03/oish.pdfMisc.http://www.dcsc.tudelft.nl/Research/Software/index.htmlAstronomySaturn and Titan trajectories ... MALTAB astronomy/~abrecht/Matlab-codes/AudioMA Toolbox for Matlab Implementing Similarity Measures for Audiohttp://www.oefai.at/~elias/ma/index.htmlMAD - Matlab Auditory Demonstrations/~martin/MAD/docs/mad.htmMusic Analysis - Toolbox for Matlab : Feature Extraction from Raw Audio Signals for Content-Based Music Retrihttp://www.ai.univie.ac.at/~elias/ma/WarpTB - Matlab Toolbox for Warped DSPBy Aki Härmä and Matti Karjalainenhttp://www.acoustics.hut.fi/software/warp/MATLAB-related Softwarehttp://www.dpmi.tu-graz.ac.at/~schloegl/matlab/Biomedical Signal data formats (EEG machine specific file formats with Matlab import routines)http://www.dpmi.tu-graz.ac.at/~schloegl/matlab/eeg/MPEG Encoding library for MATLAB Movies (Created by David Foti)It enables MATLAB users to read (MPGREAD) or write (MPGWRITE) MPEG movies. That should help Video Quality project.Filter Design packagehttp://www.ee.ryerson.ca:8080/~mzeytin/dfp/index.htmlOctave by Christophe COUVREUR (Generates normalized A-weigthing, C-weighting, octave and one-third-octave digital filters)/matlabcentral/fileexchange/loadFile.do?objectType=file&object Id=69Source Coding MATLAB Toolbox/users/kieffer/programs.htmlBio Medical Informatics (Top)CGH-Plotter: MATLAB Toolbox for CGH-data AnalysisCode: http://sigwww.cs.tut.fi/TICSP/CGH-Plotter/Poster: http://sigwww.cs.tut.fi/TICSP/CSB2003/Posteri_CGH_Plotter.pdfThe Brain Imaging Software Toolboxhttp://www.bic.mni.mcgill.ca/software/MRI Brain Segmentation/matlabcentral/fileexchange/loadFile.do?objectId=4879Chemometrics (providing PCA) (Top)Matlab Molecular Biology & Evolution Toolbox(Toolbox Enables Evolutionary Biologists to Analyze and View DNA and Protein Sequences) James J. Caihttp://www.pmarneffei.hku.hk/mbetoolbox/Toolbox provided by Prof. Massart research grouphttp://minf.vub.ac.be/~fabi/publiek/Useful collection of routines from Prof age smilde research grouphttp://www-its.chem.uva.nl/research/pacMultivariate Toolbox written by Rune Mathisen/~mvartools/index.htmlMatlab code and datasetshttp://www.acc.umu.se/~tnkjtg/chemometrics/dataset.htmlChaos (Top)Chaotic Systems Toolbox/matlabcentral/fileexchange/loadFile.do?objectId=1597&objectT ype=file#HOSA Toolboxhttp://www.mathworks.nl/matlabcentral/fileexchange/loadFile.do?objectId=3013&objectTy pe=fileChemistry (Top)MetMAP - (Metabolical Modeling, Analysis and oPtimization alias Met. M. A. P.)http://webpages.ull.es/users/sympbst/pag_ing/pag_metmap/index.htmDoseLab - A set of software programs for quantitative comparison of measured and computed radiation dose distributions/GenBank Overview/Genbank/GenbankOverview.htmlMatlab: /matlabcentral/fileexchange/loadFile.do?objectId=1139CodingCode for the estimation of Scaling Exponentshttp://www.cubinlab.ee.mu.oz.au/~darryl/secondorder_code.htmlControl (Top)Control Tutorial for Matlab/group/ctm/AnotherCommunications (Top)Channel Learning Architecture toolbox(This Matlab toolbox is a supplement to the article "HiperLearn: A High Performance Learning Architecture")http://www.isy.liu.se/cvl/Projects/hiperlearn/Source Coding MATLAB Toolbox/users/kieffer/programs.htmlTCP/UDP/IP Toolbox 2.0.4/matlabcentral/fileexchange/loadFile.do?objectId=345&objectT ype=fileHome Networking Basis: Transmission Environments and Wired/Wireless Protocols Walter Y. Chen/support/books/book5295.jsp?category=new&language=-1MATLAB M-files and Simulink models/matlabcentral/fileexchange/loadFile.do?objectId=3834&object Type=file•OPNML/MATLAB Facilities/OPNML_Matlab/Mesh Generation/home/vavasis/qmg-home.htmlOpenFEM : An Open-Source Finite Element Toolbox/CALFEM is an interactive computer program for teaching the finite element method (FEM)http://www.byggmek.lth.se/Calfem/frinfo.htmThe Engineering Vibration Toolbox/people/faculty/jslater/vtoolbox/vtoolbox.htmlSaGA - Spatial and Geometric Analysis Toolboxby Kirill K. Pankratov/~glenn/kirill/saga.htmlMexCDF and NetCDF Toolbox For Matlab-5&6/staffpages/cdenham/public_html/MexCDF/nc4ml5.htmlCUEDSID: Cambridge University System Identification Toolbox/jmm/cuedsid/Kriging Toolbox/software/Geostats_software/MATLAB_KRIGING_TOOLBOX.htmMonte Carlo (Dr Nando)http://www.cs.ubc.ca/~nando/software.htmlRIOTS - The Most Powerful Optimal Control Problem Solver/~adam/RIOTS/ExcelMATLAB xlsheets/matlabcentral/fileexchange/loadFile.do?objectId=4474&objectTy pe=filewrite2excel/matlabcentral/fileexchange/loadFile.do?objectId=4414&objectTy pe=fileFinite Element Modeling (FEM) (Top)OpenFEM - An Open-Source Finite Element Toolbox/NLFET - nonlinear finite element toolbox for MATLAB ( framework for setting up, solving, and interpreting results for nonlinear static and dynamic finite element analysis.)/GetFEM - C++ library for finite element methods elementary computations with a Matlabinterfacehttp://www.gmm.insa-tlse.fr/getfem/FELIPE - FEA package to view results ( contains neat interface to MATLA/~blstmbr/felipe/Finance (Top)A NEW MATLAB-BASED TOOLBOX FOR COMPUTER AIDED DYNAMIC TECHNICAL TRADINGStephanos Papadamou and George StephanidesDepartment of Applied Informatics, University Of Macedonia Economic & Social Sciences, Thessaloniki, Greece/fen31/one_time_articles/dynamic_tech_trade_matlab6.htm Paper: :8089/eps/prog/papers/0201/0201001.pdfCompEcon Toolbox for Matlab/~pfackler/compecon/toolbox.htmlGenetic Algorithms (Top)The Genetic Algorithm Optimization Toolbox (GAOT) for Matlab 5/mirage/GAToolBox/gaot/Genetic Algorithm ToolboxWritten & distributed by Andy Chipperfield (Sheffield University, UK)/uni/projects/gaipp/gatbx.htmlManual: /~gaipp/ga-toolbox/manual.pdfGenetic and Evolutionary Algorithm Toolbox (GEATbx)/Evolutionary Algorithms for MATLAB/links/ea_matlab.htmlGenetic/Evolutionary Algorithms for MATLABhttp://www.systemtechnik.tu-ilmenau.de/~pohlheim/EA_Matlab/ea_matlab.html GraphicsVideoToolbox (C routines for visual psychophysics on Macs by Denis Pelli)/VideoToolbox/Paper: /pelli/pubs/pelli1997videotoolbox.pdf4D toolbox/~daniel/links/matlab/4DToolbox.htmlImages (Top)Eyelink Toolbox/eyelinktoolbox/Paper: /eyelinktoolbox/EyelinkToolbox.pdfCellStats: Automated statistical analysis of color-stained cell images in Matlabhttp://sigwww.cs.tut.fi/TICSP/CellStats/SDC Morphology Toolbox for MATLAB (powerful collection of latest state-of-the-art gray-scale morphological tools that can be applied to image segmentation, non-linear filtering, pattern recognition and image analysis)/Image Acquisition Toolbox/products/imaq/Halftoning Toolbox for MATLAB/~bevans/projects/halftoning/toolbox/index.htmlDIPimage - A Scientific Image Processing Toolbox for MATLABhttp://www.ph.tn.tudelft.nl/DIPlib/dipimage_1.htmlPNM Toolboxhttp://home.online.no/~pjacklam/matlab/software/pnm/index.htmlAnotherICA / KICA and KPCA (Top)ICA TU Toolboxhttp://mole.imm.dtu.dk/toolbox/menu.htmlMISEP Linear and Nonlinear ICA Toolboxhttp://neural.inesc-id.pt/~lba/ica/mitoolbox.htmlKernel Independant Component Analysis/~fbach/kernel-ica/index.htmMatlab: kernel-ica version 1.2KPCA- Please check the software section of kernel machines.KernelStatistical Pattern Recognition Toolboxhttp://cmp.felk.cvut.cz/~xfrancv/stprtool/MATLABArsenal A MATLAB Wrapper for Classification/tmp/MATLABArsenal.htmMarkov (Top)MapHMMBOX 1.1 - Matlab toolbox for Hidden Markov Modelling using Max. Aposteriori EM Prerequisites: Matlab 5.0, Netlab. Last Updated: 18 March 2002./~parg/software/maphmmbox_1_1.tarHMMBOX 4.1 - Matlab toolbox for Hidden Markov Modelling using Variational Bayes Prerequisites: Matlab 5.0,Netlab. Last Updated: 15 February 2002../~parg/software/hmmbox_3_2.tar/~parg/software/hmmbox_4_1.tarMarkov Decision Process (MDP) Toolbox for MatlabKevin Murphy, 1999/~murphyk/Software/MDP/MDP.zipMarkov Decision Process (MDP) Toolbox v1.0 for MATLABhttp://www.inra.fr/bia/T/MDPtoolbox/Hidden Markov Model (HMM) Toolbox for Matlab/~murphyk/Software/HMM/hmm.htmlBayes Net Toolbox for Matlab/~murphyk/Software/BNT/bnt.htmlMedical (Top)EEGLAB Open Source Matlab Toolbox for Physiological Research (formerly ICA/EEG Matlabtoolbox)/~scott/ica.htmlMATLAB Biomedical Signal Processing Toolbox/Toolbox/Powerful package for neurophysiological data analysis ( Igor Kagan webpage)/Matlab/Unitret.htmlEEG / MRI Matlab Toolbox/Microarray data analysis toolbox (MDAT): for normalization, adjustment and analysis of gene expression_r data.Knowlton N, Dozmorov IM, Centola M. Department of Arthritis and Immunology, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA 73104. We introduce a novel Matlab toolbox for microarray data analysis. This toolbox uses normalization based upon a normally distributed background and differential gene expression_r based on 5 statistical measures. The objects in this toolbox are open source and can be implemented to suit your application. AVAILABILITY: MDAT v1.0 is a Matlab toolbox and requires Matlab to run. MDAT is freely available at:/publications/2004/knowlton/MDAT.zipMIDI (Top)MIDI Toolbox version 1.0 (GNU General Public License)http://www.jyu.fi/musica/miditoolbox/Misc. (Top)MATLAB-The Graphing Tool/~abrecht/matlab.html3-D Circuits The Circuit Animation Toolbox for MATLAB/other/3Dcircuits/SendMailhttp://carol.wins.uva.nl/~portegie/matlab/sendmail/Coolplothttp://www.reimeika.ca/marco/matlab/coolplots.htmlMPI (Matlab Parallel Interface)Cornell Multitask Toolbox for MATLAB/Services/Software/CMTM/Beolab Toolbox for v6.5Thomas Abrahamsson (Professor, Chalmers University of Technology, Applied Mechanics,Göteborg, Sweden)http://www.mathworks.nl/matlabcentral/fileexchange/loadFile.do?objectId=1216&objectType =filePARMATLABNeural Networks (Top)SOM Toolboxhttp://www.cis.hut.fi/projects/somtoolbox/Bayes Net Toolbox for Matlab/~murphyk/Software/BNT/bnt.htmlNetLab/netlab/Random Neural Networks/~ahossam/rnnsimv2/ftp: ftp:///pub/contrib/v5/nnet/rnnsimv2/NNSYSID Toolbox (tools for neural network based identification of nonlinear dynamic systems) http://www.iau.dtu.dk/research/control/nnsysid.htmlOceanography (Top)WAFO. Wave Analysis for Fatigue and Oceanographyhttp://www.maths.lth.se/matstat/wafo/ADCP toolbox for MATLAB (USGS, USA)Presented at the Hydroacoustics Workshop in Tampa and at ADCP's in Action in San Diego /operations/stg/pubs/ADCPtoolsSEA-MAT - Matlab Tools for Oceanographic AnalysisA collaborative effort to organize and distribute Matlab tools for the Oceanographic Community /Ocean Toolboxhttp://www.mar.dfo-mpo.gc.ca/science/ocean/epsonde/programming.htmlEUGENE D. GALLAGHER(Associate Professor, Environmental, Coastal & Ocean Sciences)/edgwebp.htmOptimization (Top)MODCONS - a MATLAB Toolbox for Multi-Objective Control System Design/mecheng/jfw/modcons.htmlLazy Learning Packagehttp://iridia.ulb.ac.be/~lazy/SDPT3 version 3.02 -- a MATLAB software for semidefinite-quadratic-linear programming .sg/~mattohkc/sdpt3.htmlMinimum Enclosing Balls: Matlab Code/meb/SOSTOOLS Sum of Squares Optimi zation Toolbox for MATLAB User’s guide/sostools/sostools.pdfPSOt - a Particle Swarm Optimization Toolbox for use with MatlabBy Brian Birge ... A Particle Swarm Optimization Toolbox (PSOt) for use with the Matlab scientific programming environment has been developed. PSO isintroduced briefly and then the use of the toolbox is explained with some examples. A link to downloadable code is provided.Plot/software/plotting/gbplot/Signal Processing (Top)Filter Design with Motorola DSP56Khttp://www.ee.ryerson.ca:8080/~mzeytin/dfp/index.htmlChange Detection and Adaptive Filtering Toolboxhttp://www.sigmoid.se/Signal Processing Toolbox/products/signal/ICA TU Toolboxhttp://mole.imm.dtu.dk/toolbox/menu.htmlTime-Frequency Toolbox for Matlabhttp://crttsn.univ-nantes.fr/~auger/tftb.htmlVoiceBox - Speech Processing Toolbox/hp/staff/dmb/voicebox/voicebox.htmlLeast Squared - Support Vector Machines (LS-SVM)http://www.esat.kuleuven.ac.be/sista/lssvmlab/WaveLab802 : the Wavelet ToolboxBy David Donoho, Mark Reynold Duncan, Xiaoming Huo, Ofer Levi /~wavelab/Time-series Matlab scriptshttp://wise-obs.tau.ac.il/~eran/MATLAB/TimeseriesCon.htmlUvi_Wave Wavelet Toolbox Home Pagehttp://www.gts.tsc.uvigo.es/~wavelets/index.htmlAnotherSupport Vector Machine (Top)MATLAB Support Vector Machine ToolboxDr Gavin CawleySchool of Information Systems, University of East Anglia/~gcc/svm/toolbox/LS-SVM - SISTASVM toolboxes/dmi/svm/LSVM Lagrangian Support Vector Machine/dmi/lsvm/Statistics (Top)Logistic regression/SAGA/software/saga/Multi-Parametric Toolbox (MPT) A tool (not only) for multi-parametric optimization. http://control.ee.ethz.ch/~mpt/ARfit: A Matlab package for the estimation of parameters and eigenmodes of multivariate autoregressive modelshttp://www.mat.univie.ac.at/~neum/software/arfit/The Dimensional Analysis Toolbox for MATLABHome: http://www.sbrs.de/Paper: http://www.isd.uni-stuttgart.de/~brueckner/Papers/similarity2002.pdfFATHOM for Matlab/personal/djones/PLS-toolbox/Multivariate analysis toolbox (N-way Toolbox - paper)http://www.models.kvl.dk/source/nwaytoolbox/index.aspClassification Toolbox for Matlabhttp://tiger.technion.ac.il/~eladyt/classification/index.htmMatlab toolbox for Robust Calibrationhttp://www.wis.kuleuven.ac.be/stat/robust/toolbox.htmlStatistical Parametric Mapping/spm/spm2.htmlEVIM: A Software Package for Extreme Value Analysis in Matlabby Ramazan Gençay, Faruk Selcuk and Abdurrahman Ulugulyagci, 2001.Manual (pdf file) evim.pdf - Software (zip file) evim.zipTime Series Analysishttp://www.dpmi.tu-graz.ac.at/~schloegl/matlab/tsa/Bayes Net Toolbox for MatlabWritten by Kevin Murphy/~murphyk/Software/BNT/bnt.htmlOther: /information/toolboxes.htmlARfit: A Matlab package for the estimation of parameters and eigenmodes of multivariate autoregressive models/~tapio/arfit/M-Fithttp://www.ill.fr/tas/matlab/doc/mfit4/mfit.htmlDimensional Analysis Toolbox for Matlab/The NaN-toolbox: A statistic-toolbox for Octave and Matlab®... handles data with and without MISSING VALUES.http://www-dpmi.tu-graz.ac.at/~schloegl/matlab/NaN/Iterative Methods for Optimization: Matlab Codes/~ctk/matlab_darts.htmlMultiscale Shape Analysis (MSA) Matlab Toolbox 2000p.br/~cesar/projects/multiscale/Multivariate Ecological & Oceanographic Data Analysis (FATHOM)From David Jones/personal/djones/glmlab (Generalized Linear Models in MATLA.au/staff/dunn/glmlab/glmlab.htmlSpacial and Geometric Analysis (SaGA) toolboxInteresting audio links with FAQ, VC++, on the topic机器学习网站北京大学视觉与听觉信息处理实验室北京邮电大学模式识别与智能系统学科复旦大学智能信息处理开放实验室IEEE Computer Society北京映象站点计算机科学论坛机器人足球赛模式识别国家重点实验室南京航空航天大学模式识别与神经计算实验室- PARNEC南京大学机器学习与数据挖掘研究所- LAMDA南京大学人工智能实验室南京大学软件新技术国家重点实验室人工生命之园数据挖掘研究院微软亚洲研究院中国科技大学人工智能中心中科院计算所中科院计算所生物信息学实验室中科院软件所中科院自动化所中科院自动化所人工智能实验室ACL Special Interest Group on Natural Language Learning (SIGNLL)ACMACM Digital LibraryACM SIGARTACM SIGIRACM SIGKDDACM SIGMODAdaptive Computation Group at University of New MexicoAI at Johns HopkinsAI BibliographiesAI Topics: A dynamic online library of introductory information about artificial intelligence Ant Colony OptimizationARIES Laboratory: Advanced Research in Intelligent Educational SystemsArtificial Intelligence Research in Environmental Sciences (AIRIES)Austrian Research Institute for AI (OFAI)Back Issues of Neuron DigestBibFinder: a computer science bibliography search engine integrating many other engines BioAPI ConsortiumBiological and Computational Learning Center at MITBiometrics ConsortiumBoosting siteBrain-Style Information Systems Research Group at RIKEN Brain Science Institute, Japan British Computer Society Specialist Group on Expert SystemsCanadian Society for Computational Studies of Intelligence (CSCSI)CI Collection of BibTex DatabasesCITE, the first-stop source for computational intelligence information and services on the web Classification Society of North AmericaCMU Advanced Multimedia Processing GroupCMU Web->KB ProjectCognitive and Neural Systems Department of Boston UniversityCognitive Sciences Eprint Archive (CogPrints)COLT: Computational Learning TheoryComputational Neural Engineering Laboratory at the University of FloridaComputational Neurobiology Lab at California, USAComputer Science Department of National University of SingaporeData Mining Server Online held by Rudjer Boskovic InstituteDatabase Group at Simon Frazer University, CanadaDBLP: Computer Science BibliographyDigital Biology: about creating artificial lifeDistributed AI Unit at Queen Mary & Westfield College, University of LondonDistributed Artificial Intelligence at HUJIDSI Neural Networks group at the Université di Firenze, ItalyEA-related literature at the EvALife research group at DAIMI, University of Aarhus, Denmark Electronic Research Group at Aberdeen UniversityElsevierComputerScienceEuropean Coordinating Committee for Artificial Intelligence (ECCAI)European Network of Excellence in ML (MLnet)European Neural Network Society (ENNS)Evolutionary Computing Group at University of the West of EnglandEvolutionary Multi-Objective Optimization RepositoryExplanation-Based Learning at University of Illinoise at Urbana-ChampaignFace Detection HomepageFace Recognition Vendor TestFace Recognition HomepageFace Recognition Research CommunityFingerpassftp of Jude Shavlik's Machine Learning Group (University of Wisconsin-Madison)GA-List Searchable DatabaseGenetic Algorithms Digest ArchiveGenetic Programming BibliographyGesture Recognition HomepageHCI Bibliography Project contain extended bibliographic information (abstract, key words, table of contents, section headings) for most publications Human-Computer Interaction dating back to 1980 and selected publications before 1980IBM ResearchIEEEIEEE Computer SocietyIEEE Neural Networks SocietyIllinois Genetic Algorithms Laboratory (IlliGAL)ILP Network of ExcellenceInductive Learning at University of Illinoise at Urbana-ChampaignIntelligent Agents RepositoryIntellimedia Project at North Carolina State UniversityInteractive Artificial Intelligence ResourcesInternational Association of Pattern RecognitionInternational Biometric Industry AssociationInternational Joint Conference on Artificial Intelligence (IJCAI)International Machine Learning Society (IMLS)International Neural Network Society (INNS)Internet Softbot Research at University of WashingtonJapanese Neural Network Society (JNNS)Java Agents for Meta-Learning Group (JAM) at Computer Science Department, Columbia University, for Fraud and Intrusion Detection Using Meta-Learning AgentsKernel MachinesKnowledge Discovery MineLaboratory for Natural and Simulated Cognition at McGill University, CanadaLearning Laboratory at Carnegie Mellon UniversityLearning Robots Laboratory at Carnegie Mellon UniversityLaboratoire d'Informatique et d'Intelligence Artificielle (IIA-ENSAIS)Machine Learning Group of Sydney University, AustraliaMammographic Image Analysis SocietyMDL Research on the WebMirek's Cellebration: 1D and 2D Cellular Automata explorerMIT Artificial Intelligence LaboratoryMIT Media LaboratoryMIT Media Laboratory Vision and Modeling GroupMLNET: a European network of excellence in Machine Learning, Case-based Reasoning and Knowledge AcquisitionMLnet Machine Learning Archive at GMD includes papers, software, and data sets MIRALab at University of Geneva: leading research on virtual human simulationNeural Adaptive Control Technology (NACT)Neural Computing Research Group at Aston University, UKNeural Information Processing Group at Technical University of BerlinNIPSNIPS OnlineNeural Network Benchmarks, Technical Reports,and Source Code maintained by Scott Fahlman at CMU; source code includes Quickprop, Cascade-Correlation, Aspirin/Migraines Neural Networks FAQ by Lutz PrecheltNeural Networks FAQ by Warren S. SarleNeural Networks: Freeware and Shareware ToolsNeural Network Group at Department of Medical Physics and Biophysics, University ofNeural Network Group at Université Catholique de LouvainNeural Network Group at Eindhoven University of TechnologyNeural Network Hyperplane Animator program that allows easy visualization of training data and weights in a back-propagation neural networkNeural Networks Research at TUT/ELENeural Networks Research Centre at Helsinki University of Technology, FinlandNeural Network Speech Group at Carnegie Mellon UniversityNeural Text Classification with Neural NetworksNonlinearity and Complexity HomepageOFAI and IMKAI library information system, provided by the Department of Medical Cybernetics and Artificial Intelligence at the University of Vienna (IMKAI) and the Austrian Research Institute for Artificial Intelligence (OFAI). It contains over 36,000 items (books, research papers, conference papers, journal articles) from many subareas of AI OntoWeb: Ontology-based information exchange for knowledge management and electronic commercePortal on Neural Network ForecastingPRAG: Pattern Recognition and Application Group at University of CagliariQuest Project at IBM Almaden Research Center: an academic website focusing on classification and regression trees. Maintained by Tjen-Sien LimReinforcement Learning at Carnegie Mellon UniversityResearchIndex: NECI Scientific Literature Digital Library, indexing over 200,000 computer science articlesReVision: Reviewing Vision in the Web!RIKEN: The Institute of Physical and Chemical Research, JapanSalford SystemsSANS Studies of Artificial Neural Systems, at the Royal Institute of Technology, Sweden Santa-Fe InstituteScirus: a search engine locating scientific information on the InternetSecond Moment: The News and Business Resource for Applied AnalyticsSEL-HPC Article Archive has sections for neural networks, distributed AI, theorem proving, and a variety of other computer science topicsSOAR Project at University of Southern CaliforniaSociety for AI and StatisticsSVM of ANU CanberraSVM of Bell LabsSVM of GMD-First BerlinSVM of MITSVM of Royal Holloway CollegeSVM of University of SouthamptonSVM-workshop at NIPS97TechOnLine: TechOnLine University offers free online courses and lecturesUCI Machine Learning GroupUMASS Distributed Artificial Intelligence LaboratoryUTCS Neural Networks Research Group of Artificial Intelligence Lab, Computer Science Department, University of Texas at AustinVivisimo Document Clustering: a powerful search engine which returns clustered results Worcester Polytechnic Institute Artificial Intelligence Research Group (AIRG)Xerion neural network simulator developed and used by the connectionist group at the University of TorontoYale's CTAN Advanced Technology Center for Theoretical and Applied Neuroscience ZooLand: Artificial Life Resource。
不确定机器人系统轨迹跟踪鲁棒控制
将所提鲁棒控制方法与其他先进的机器人技术相结合，如机器学习、人工智能等，以提升机器人系统的智能化水平和自主性。
深入研究机器人系统的动力学特性和运动学约束，优化控制算法，以实现更快速、更精确的轨迹跟踪。
谢谢您的观看
THANKS
详细描述
总结词
基于观测器的鲁棒控制策略通过设计观测器来估计机器人系统的状态，并利用估计的状态信息设计控制器，以实现轨迹跟踪的鲁棒性。
详细描述
该策略通过设计观测器来估计机器人系统的状态，并利用估计的状态信息设计控制器。由于观测器能够有效地对不确定性进行补偿，因此基于观测器的鲁棒控制策略能够提高轨迹跟踪的鲁棒性。同时，该策略还具有较好的动态性能和适应能力。
实验与验证
05
采用具有不确定性的机器人系统作为实验对象，如工业机器人或服务机器人。
实验平台
实验环境
实验条件
在室内或室外环境中进行实验，模拟实际应用场景，包括静态和动态环境。
确保实验条件的一致性和可重复性，包括机器人初始状态、环境干扰、传感器噪声等。
03
02
01
实验结果
记录机器人在不同条件下的轨迹跟踪性能，包括跟踪误差、稳定性、响应时间等指标。
输出反馈鲁棒控制
通过调整控制器参数来适应系统的不确定性变化，提高系统的鲁棒性。
自适应鲁棒控制
03
模型不确定性的处理
针对机器人系统模型的不确定性，采用鲁棒控制策略，减小其对系统性能的影响。
01
不确定机器人系统的轨迹跟踪
针对具有不确定性的机器人系统，设计鲁棒控制器，实现轨迹跟踪的精确控制。
柔性冗余度机器人考虑抑振的力矩优化算法
将式 （J） 代入式 （!）得柔性冗度机器人的振动 方程
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作者简介： 毕树生， 男， （北京市 STWW 年生。北京航空航天大学 机械工程及自动化学院副教授、 博士。研究方向为微操 SHHHMJ） 作机器人系统、 机 器 人 机构 学 等。发 表 论文 IH 余篇。于靖 军， 男， STKU 年生。北京航空航天大学机械工程及自动化学院博士后 研究人员。宗光华， 男， STUJ 年生。北京航空航天大学机械工程 及自动化学院教授、 博士研究生导师。
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四足机器人动力学建模拉格朗日动力学
四足机器人动力学建模：拉格朗日动力学引言在机器人领域中，四足机器人是一种常见的机器人类型。
它们具有四条腿和能够模拟和模仿动物行走的能力。
为了实现自主步行和平稳运动，我们需要对四足机器人的动力学进行建模和分析。
本文将介绍使用拉格朗日动力学方法对四足机器人进行建模的过程和步骤。
拉格朗日动力学简介拉格朗日动力学是一种描述系统动力学行为的方法。
它基于拉格朗日原理，通过最小化系统的运动方程，求解系统中的广义坐标和约束力。
在机器人动力学中，拉格朗日动力学方法被广泛应用于建模和控制。
四足机器人动力学建模步态与坐标系在进行四足机器人动力学建模之前，首先需要确定机器人的步态和坐标系。
通常，四足机器人的步态可以分为步行和跑步两种模式。
对于步行模式，机器人的步态可以简化为前后左右四个联系稳定的点。
在这种情况下，机器人的坐标系可以选择为正前方为x轴正方向，右侧为y轴正方向，地面为z轴正方向。
运动学分析在进行动力学建模之前，需要进行机器人的运动学分析。
运动学分析可以得到机器人各个关节的位置、速度和加速度信息。
这些信息对于后续的动力学建模非常重要。
动力学建模操作要素在进行动力学建模之前，需要确定机器人系统的操作要素。
这些要素包括机器人的质量、惯性、关节约束等。
通过对这些要素的分析和建模，可以得到机器人的整体动力学方程。
拉格朗日方程拉格朗日动力学方法使用拉格朗日方程来描述系统的运动方程。
拉格朗日方程可以通过系统的动能和势能表达式得到。
对于四足机器人，为了简化模型，通常可以假设机器人为刚体，并且忽略其柔软特性。
拉格朗日方程的形式如下：L = T - V其中，L为拉格朗日函数，T为系统的动能，V为系统的势能。
动力学模拟通过对拉格朗日方程进行求解，可以得到系统的运动方程。
为了模拟机器人的动力学行为，可以使用数值方法进行迭代求解。
常见的数值方法有欧拉法和中点法等。
结论通过拉格朗日动力学方法进行建模，可以得到四足机器人的运动方程和动力学模拟。
基于模型分块逼近的三关节机器人鲁棒滑模控制
基于模型分块逼近的三关节机器人鲁棒滑模控制马莉丽;钟斌【摘要】三关节机器人结构参数、作业环境的外界干扰及结构振动等不确定因素均会造成其动力学模型不确定，导致机器人关节位置镇定或轨迹跟踪控制器的设计具有一定的难度。
为此，设计三个RBF（Radical Basis Function）神经网络分别对机器人不确定模型中的三个不确定项进行分块逼近，得到三个不确定项的估计信息，从而得出机器人估计模型，神经网络的权值采用适应算法。
针对机器人估计模型设计鲁棒滑模控制律，其中鲁棒项用于克服神经网络建模误差。
通过定义 Lya-punov函数，证明了控制系统是稳定的。
实验结果也表明了三关节均约在1 s时达到期望位置或跟踪期望轨迹，位置镇定误差或轨迹跟踪误差也快速、稳定地趋于零。
%Generally,the dynamic model of robot with three-j oint is undetermined due to three-j oint robot’s uncertain structure parameters,working environment’s external interfere and struc-tural vibration.Accordingly,it is difficult to control the robot’s joints’position stabilizing and traj ectory tracking and controller’s design due to the dynamic model’s uncertainty.Therefore, three designed RBF(Radical Basis Function)neural networks are used to respectively model the three undetermined terms of the undetermined robot dynamic model,with partition approxima-ting the three-joint robot.Three undetermined terms’estimation information is respectively ob-tained,with the robot’s estimation model obtained.The neural networks’weights are obtained through the adaptive algorithm.The robust sliding mode control law is designed based on the ro-bot’s estimation model.The control law’srobust term is used to overcome the neural networks’ modeling er ror.The control system’s stability is proved by defining Lyapunov function.The simulation experiments test verifies that three joints can trace ideal trajectory and reach an ideal position in 1 s,and stabilization error and tracking error can fast and stably approximate to zero.【期刊名称】《西安理工大学学报》【年(卷),期】2016(032)004【总页数】6页(P437-442)【关键词】三关节机器人;模型分块逼近;关节控制;RBF神经网络【作者】马莉丽;钟斌【作者单位】中国人民武装警察部队工程大学装备工程学院，陕西西安 710086;中国人民武装警察部队工程大学装备工程学院，陕西西安 710086【正文语种】中文【中图分类】TP242.2三关节机器人(以下简称机器人)结构紧凑，所占空间小，灵活性强，工作空间较大，避障性好，广泛应用于工业机器人中。
并联机器人正运动学与NURBS轨迹规划
282机械设计与制造Machinery Design&M anufacture第4期2021年4月并联机器人正运动学与NURBS轨迹规划张皓宇\刘晓伟、任川、赵彬w(1.辽宁省气象信息中心，辽宁沈阳110168:2.沈阳新松系统自动化股份有限公司，辽宁沈阳110168;3.东北大学信息科学与工程学院，辽宁沈阳110819)摘要：并联机器人是一种具有高栽荷自重比的封闭式运动结构，针对并联机器人运动控制和N U R B S轨迹问题进行了深入的研究，首先从并联机器人的逆运动学问题进行了解析方法的求解其次,针对正运动学（F KP)在教学上是难以解决问题，提出了一种多层感知器进行反向传播学习的神经网络进行实时求解。
再次，开发了基于N U R B S的通用插补器，它可以处理任何类型的几何图形使得机器人运动轨迹平滑。
最后利用实验验证了运动学和N U R B S曲线求解并联机器人模型的正确性。
该策略在少数迭代和很少执行时间内，位置和方向参数的精度分别接近0.01m m和0.01。
,验证了算法的有效性和正确性。
关键词:并联机器人;N U R B S曲线;运动学;神经网络中图分类号:T H16;TP242.3文献标识码:A文章编号：1001-3997(2021 )04-0282-05Forward Kinematics Control and NURBS Trajectory Planning for Parallel RobotsZHANG Hao-yu1，UU Xiao-wei1，REN Chuan1，ZHAO Bin2.3(1.R e s e a r c h e r L e v e l S e n i o r E n g i n e e r o f M e t e o r o l o g i c a l I n f o r m a t i o n Ce nt er,L i a o n i n g Shenyang110168，China;2.SIASUNRo bot&Aut om at io n Co.,L t d.，L i a o n i n g Shenyang110168，China;3.S c h o o l o f I n f o r m a t i o n S c i e n c e&E n g i n e e r i n g,N o r t h e a s t e r n U n i v e r s i t y,L i a o n i n g Shenyang110819，China)A b s tr a c t：Parallel robot is a closed motion structure with a high load to weight ratio.In this paper^the motion control of parallel robot and NURBS trajectory are studied in depth.Firstly,the inverse kinematics o f parallel robot is solved by analytical method.Secondly,the forward kinematics(FKP)is difficult to solve mathematically9this paper proposes a multilayer perceptron back-propagation learning neural network for real-time solution.Thirdly y a universal interpolator based on NURBS is developedy which can handle any type of geometric shapes to make the robot's trajectory smooth.Finally,the correctness of kinematics and NURBS curves for solving parallel robot model is verified by experiments.The accuracy of position and direction parameters of this strategy is close to O.Q\mm and0.Q\o respectively in few iterations and f ew execution time,which verifies the effectiveness and correctness of the algorithm.Key Words-.Parallel Robot；NURBS Curve；Kinematics；Neural Networkl引言并联机构学理论研究蓬勃发展，并联机器人的运动学理论 也不断得到丰富"-31。
MRB-PAM 康复柔性关节设计与分析
价值工程0引言随着时代的进步和科学技术的不断进步，人们的身体健康问题越来越受到重视，尤其是在人体瘫痪的辅助治疗上。
在后期自主康复的过程中，为了降低医疗患者家庭的生活费用，进而减轻治疗带来的心理压力，减少大量公共医疗资源的消耗，辅助人体的康复机器人应运而生。
康复机器人是工业机器人和医用机器人的结合[1]。
因此，目前康复机器人的驱动手段主要以电机等，控制机器人带动人体做运动。
但当机器人应用于人体时，电机驱动人体，使得施加力和刚强度过大，对患者身体造成二次损伤。
这样就产生了柔软的关节，广泛应用于医疗、制造、救援等领域。
例如外骨骼机器人、柔性机械臂和足式机器人等机器人[2，3]。
近几年国内越来越多的院校和科研机构对康复设备（柔性关节机器人）进行了研究，并取得了一系列的研究成果。
国内外众多学者基于气动肌肉群拮抗驱动装置设计了一种3自由度球关节结构机器人[4，5]；设计了一种捆扎交错式气动人工肌肉执行器[6]，以此来提高工作效率；在“cheetah ”机器人系统中[7]，使用拮抗式气动人工肌肉关节结构。
也将拮抗式或单/多根气动人工肌肉与改进的多种机构进行结合，设计出了许多新型的柔性关节，包括采用滑轮结构将弹性元件与驱动元件分开布置的气动人工肌肉驱动串联弹性关节[8]、通过利用一组平行的气动人工肌肉束拉动滑板-连杆机构产生旋转运动的PAM-actuated 重载机械臂[9]、两根气动人工肌肉和两根弹簧并联的四杆关节机构[10，11]等等。
1机械设计人体下肢膝关节自由度是1，即，如图1。
只完成一个转动输出。
关节总体可将其分成三个部分，包括：气动人工肌肉驱动部分；磁流变液制动器刚性调节部分；连杆联动部分。
即：在人工气动肌肉在拉伸的过程中，连接着磁流变液制动器，通过调节引入的电压电流，改变制动器的阻抗强度，给人工气动肌肉拉伸的柔性不稳定性，提供一定的转动刚度，稳定的将驱动转力传送到小腿骨的关节，带动患者稳定行走。
2运动分析在本文的MRB-PAM 复合驱动仿生肩关节中，大腿端为固定端，气动人工肌肉、磁流变制动器与小腿端为运动部件，运动部件的动能E ki 为（1）———————————————————————作者简介:李安平（1998-），男，山东潍坊人，研究生，硕士，研究方向为机械。
两自由度机械臂动力学模型的建模与控制
2020(Sum. No 207)2020年第03期(总第207期)信息通信INFORMATION & COMMUNICATIONS两自由度机械臂动力学模型的建模与控制王磊，陈辰生,张文文(同济大学中德学院，上海202001)摘要：机器人系统建模在布局评估、合理性研究、动画展示以及离线编程等方面有越来越广的应用。
文章对两个自由度 机械臂基于拉格朗日动力学方程，进行建模。
通过建立的模型，分析了重力对两自由度机械臂的影响以及在重力作用下不在稳定位置的机械臂的运动轨迹。
基于机械臂的数学模型，基于Simulink 仿真环境，建立机械臂的仿真模型。
采用逆 动力学方法对机械臂进行控制，观察其对机械臂的控制效果⑴。
通过仿真建模，可以了解机械臂动力学模型以及机械臂动态模型的控制问题。
关键词:动力学模型;数学模型推导;机器人建模;重力分析;逆动力学控制中图分类号:TP241 文献标识码:A 文章编号:1673-1131(2020 )03-0040-03The simulation and control of two ・degree-of freedom robot armWang Lei, Chen Chensheng, Zhang Wenwen(Sino German College of Tongji University, Shanghai 201804)Abstract: The simulation of robot systems is becoming very popular, it can be used for layout evaluation, feasibility studies, presentations with animation and off-line programming 121. In this paper, two degrees of freedom manipulators are modeled based on Lagrange^ dynamic equation. Through the established model, the influence of g ravity on the two-degree-of-freedom manip ulator and the trajectory of the manipulator that is not in a stable position under the action of gravity are analyzed. Based on the mathematical model of the robotic arm and the Simulink simulation environment, a simulation model of the robotic arm is es tablished. The inverse dynamics method was used to control the manipulator, and the control effect on the manipulator was observed. Through simulation modeling, you can understand the dynamics model of the robotic arm and the control problems of the dynamic model of t he robotic arm.Key words: dynamic model; mathematical model derivation; robot modeling; gravity analysis; inverse dynamic control0引言机器人学是一门特殊的工程科学，其中包括机器人设计、建模、控制以及使用。
基于牛顿-拉夫逊迭代法的6自由度机器人逆解算法
（ 江南 大 学 通 信 与 控 制 工 程 学 院 ， 苏 无 锡 ２４ ２ ） 江 １１ ２
摘
要 ：为解决一般 ６自由度旋转关节机器人逆运动学 问题 ， 出了一种用牛顿一 提 拉夫逊迭代 法逐次逼近
目标位姿的逆解算法。根据正运动学方程建立稚克 比矩 阵， 采用基于豪斯霍尔 德的 Ｓ Ｄ分解求 其伪逆来 Ｖ 避免雅克 比矩阵的奇异性问题 ， 通过建 立迭代规则并逐次迭代找到最优的逆运动学单解 ， 际应用时无需 实
Байду номын сангаас
误差 ， 甚至一些机器 人在设计 时就不符 合 Ｐｅｅ 准则 。针 ｉ ｒ ｐ
ｓ ｓｅ Ｔｈｅ ｃ ｒｅ ｐｏ ｄ ｎ ｅ ｔ ｈ ｗ ｈ ｔｔ ｌｏ ｔ ｍ ｓｒａ —ｉ ｉｈ ｃ ｎ ｍｅ ｔｓ ｓｅ ｒ ｑ ｒ ｍｅ ｔ． ｔｃ ｎ ｂ ｙ ｔｍ． ｏ ｒ ｓ ｎ ｉ ｇ ｔｓｓｓ ｏ ｔ ａ ｈｅａｇ ｒ ｈ ｉ ｅ ｌｔｍｅｗｈ ｃ ａ ｅ ｙ ｔｍ ｅ ｕｉｅ ｎｓ Ｉ ａ ｅ ｉ
ａｐｉ ａ ｔ ｅｒｂｔ ｏ ｔ ｌ ｙｔ ６ｄｇｅ ｆｒ ｄｍ（ Ｏ ）ｒｔ ｉｏ ｐｌ ｄｔ ｒｌ ｉ ｏ ｃｎ ｏ ｓｓ ｍ； ｅｒｅｏ ｅ ｏ Ｄ Ｆ ｏ ｒ ｊ ｎ ｔ ｅ ｏ ｅ －ｍ ｏ ｒ ｅ ｆｅ ａ ｏ ｙ Ｋｅ ｏ ｄ ：ｒ ｏ； ｏｏ ｏｔ ｌ ｄｆｒｎｉ ｏｏ ； ｅｒｅｏ ｅｄ ｍ（ Ｏ ）ｒｔ ｉｔ ｙｗ ｒｓ ｏ ｔ ｍ ｔ ｎｃｎ ｏ； ｉ ｅｔ ｍ ｔｎ ６ｄ ｇ ｆｒｅｏ Ｄ Ｆ ｏ ｒ ｊ ｎ ｂ ｉ ｒ ｅ ｌ ａ ｉ ｅ ｆ ａ ｏ ｙ ０ 引 言
Ａｂ ｔａ ｔ ｏｒｓｌ ｅｉｖｒｅｋ ｅ ｔ ｓ ｒ ｌ ｆ ｈ ｅ ｅ ｌ － Ｏ ｔ ｙｊｉ ｂ ｔａ ｖ ｒ ｌｏ ｔｍ ｓ ｃ ：Ｔ ｅｏ ｅｔ ｅ ｉ ｍａ ｃ ｏ ｅ ｏ ｔｅｇｎ ｒ Ｄ Ｆ ｒ ａ ｎ ｒ ｏ，ｎｉ ｅ ｅａ ｒｈ ｒ ｖ ｈ ｎ ｓ ｎ ｉ ｐ ｂ ｍ ａ６ ｏ ｒ ｏ ｔｏ ｎ ｓ ｇｉ
机器人手臂的动力学建模与运动控制研究
机器人手臂的动力学建模与运动控制研究随着科技的不断进步和发展，机器人技术日益成熟，并在各个领域得到了广泛的应用。
在许多需要高精度操作和自动化生产的场景中，机器人手臂成为关键的装置。
机器人手臂的动力学建模与运动控制是机器人领域中的重要研究方向，本文将从动力学建模和运动控制两个方面进行探讨。
动力学建模是指研究机器人手臂在运动过程中所受到的力和力矩以及位置、速度和加速度之间的关系。
动力学建模的目的是准确描述机器人手臂的运动特性，为后续的运动控制提供基础。
在动力学建模中，通常会涉及到刚体力学、运动学和动力学等相关知识。
对于机器人手臂的动力学建模，一种常见的方法是使用拉格朗日动力学方程。
拉格朗日动力学方程可以通过建立系统的拉格朗日函数和广义力的关系来描述机器人手臂的运动。
通过求解和分析拉格朗日动力学方程，可以得到机器人手臂的位置、速度和加速度等动力学参数。
同时，还可以得到机器人手臂所受到的力和力矩。
除了使用拉格朗日动力学方程外，还有其他一些动力学建模方法，如牛顿-欧拉动力学方程和Kane方法等。
这些方法在不同的应用场景下具有各自的优势。
通过选择合适的动力学建模方法，可以更好地描述机器人手臂的运动特性，为后续的运动控制研究提供可靠的理论基础。
在动力学建模的基础上，进一步研究机器人手臂的运动控制也是至关重要的。
运动控制的目标是通过对机器人手臂的输入信号进行控制，使其达到所期望的位置、速度和加速度等目标。
在运动控制中，通常涉及到控制算法的设计和控制器的实现。
控制算法的设计是运动控制中的关键问题。
常用的控制算法包括比例-积分-微分控制（PID控制）、模型预测控制（MPC）和自适应控制等。
这些算法根据机器人手臂的运动特性和控制要求，通过对输入信号进行优化和调整，实现对机器人手臂的精确控制。
同时，还可以考虑到不同的环境和外界干扰因素，提高机器人手臂的抗干扰能力。
控制器的实现是运动控制中的另一个关键问题。
通常采用的控制器包括PID控制器、模糊控制器和神经网络控制器等。
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IEEETRANSACTIONSONNEURALNETWORKS,VOL.10,NO.5,SEPTEMBER19991123ALagrangianNetworkforKinematicControlofRedundantRobotManipulators
JunWang,SeniorMember,IEEE,QingniHu,andDanchiJiang
Abstract—Arecurrentneuralnetwork,calledtheLagrangiannetwork,ispresentedforthekinematiccontrolofredundantrobotmanipulators.Theoptimalredundancyresolutionisde-terminedbytheLagrangiannetworkthroughreal-timesolutiontotheinversekinematicsproblemformulatedasaquadraticoptimizationproblem.Whilethesignalforadesiredvelocityoftheend-effectorisfedintotheinputsoftheLagrangiannetwork,itgeneratesthejointvelocityvectorofthemanipulatorinitsoutputsalongwiththeassociatedLagrangemultipliers.TheproposedLagrangiannetworkisshowntobecapableofasymp-totictrackingforthemotioncontrolofkinematicallyredundantmanipulators.
IndexTerms—Asymptoticstability,kinematiccontrol,kine-maticallyredundantmanipulators,optimizationmethod,recur-rentneuralnetworks.
I.INTRODUCTION
INROBOTICmotionplanningandcontrol,thesolutionsto
thekinematicsproblemsareessentialtoachievethegoalsofaroboticoperation.TheforwardkinematicsprobleminroboticsisconcernedwiththetransformationofpositionandorientationinformationinajointspacetoaCartesianspacedescribedbyaforwardkinematicsequation
isanisanisacontinuousnonlinearfunctionwhosestructureandparametersareknownforagivenmanipulator.Theinversekinematicsproblemistofindthejointvariablesgiventhedesiredpositionsandorientationsoftheend-effectorthroughtheinversemappingoftheforwardkinematicsequation(1)1124IEEETRANSACTIONSONNEURALNETWORKS,VOL.10,NO.5,SEPTEMBER1999control[24],[31],[38],[41]–[43],[45],[49],[50]–[54].Unlikefeedforwardneuralnetworks,mostrecurrentneuralnetworksdonotneedoff-linesupervisedlearningandthusaremoresuitableforreal-timerobotcontrolinuncertainenvironments.Inthispaper,arecurrentneuralnetwork,calledtheLa-grangiannetwork,ispresentedforthekinematiccontrolofredundantmanipulators.TheproposedLagrangiannetworkexplicitlyminimizesaweightednormofthejointvelocityvectorwhilekeepingthelinearrelationbetweenandsatisfied.Itisshowntobeasymptoticallystableandcapableofsolvingtheinversekinematicsprobleminrealtime.TheoperatingcharacteristicsandperformanceoftheLagrangiannetworkaredemonstratedbyuseofsimulationresults.Therestofthispaperisorganizedinfivesections.InSectionII,theinversekinematicsproblemisformulatedasatime-varyingquadraticprogrammingproblemwithequal-ityconstraints.InSectionIII,theenergyfunctionanddy-namicequationoftheLagrangiannetworkaredescribed.InSectionIV,theLagrangiannetworkisproventohavethecapabilityofasymptotictracking.InSectionV,thesimulationresultsoftheLagrangiannetworktocontrolaseven-degree-of-freedom(DOF)manipulatorarediscussed.Finally,SectionVIconcludesthepaperwithfinalremarks.
II.PROBLEMFORMULATION
Inordertodeterminethrough(3),thejointvelocityvectorneedstobecomputed.Onewaytodetermineisasfollows[9]:
(4)whereisanisanidentitymatrix,and-vectorofarbitrarytime-varyingvariables.Thismethodentailsthecomputationoftime-varyingpseudoinverse
(5)subjectto(6)
wherethesuperscriptisansymmetricpositive-definiteweightingmatrix.Inparticular,if
.If
isan.
Bysettingthepartialderivativesof(8)1,thenrewriting(8)and(9)inacombinedmatrixform,wehave
and,anandan,respectivelyThedynamicequationsoftheLagranexpressedbythefollowingtime-varequations:
(11)(12)
where
is.Equa-tion(11)alsoshowsthatthetime-vamatrixfromtheneuronsrepresentedtotheneuronsrepresentedbyis
totheneuronsrepresenteis.Fig.1illustratekinematiccontrolprocessbasedontInthiscontext,thedesiredvelociyisinputintotheLagrangiannetwork,andatthesanetworkoutputsthecomputedjointv.
IV.STABILITYANALYSIS
Writteninacombinedformat,theLabedescribedasthefollowingtime-vsystem:
,,andWANGetal.:LAGRANGIANNETWORKFORKINEMATICCONTROL1125Fig.1.Blockdiagramoftheneural-networkapproachtorobotkinematicscontrol.Givenaninitialpointofthesystemstartingfrom
inthe-neighborhoodofstateofthesolutionpartofcomponentsofthecorrespondingsolutionconvergestoas
term.ThefollowingtheoremgivesthestabilitypropertyoftheproposedLagrangiannetwork.Theorem1:TheLagrangiannetworkdefinedin(13)isgloballystable.Furthermore,
isaconstantpositivedefinitesymmetricmatrixandistheminimaleigenvalueofhasnoeigenvaluewithpositiverealpartorpureimaginarypart.Furthermore,iftherowrankof,thenhaspositiverealpart.Sinceandisalwaysnegativesemidefinite.Inthecaseofrealeigenvalue,ifassociatedwith,wehaveisalwaysnegativesemidefinite.T.Ifandand.ThenChooseavectorhaspureimaginarypart.Let’sathat.Ifisacomplexeigenvector