Parallel kinematic machines （PKMs） have the advantages of a compact structure,high stiffness,a low moving inertia,and a high load/weight ratio.PKMs have been intensively studied since the 1980s,and are still attract...Parallel kinematic machines （PKMs） have the advantages of a compact structure,high stiffness,a low moving inertia,and a high load/weight ratio.PKMs have been intensively studied since the 1980s,and are still attracting much attention.Compared with extensive researches focus on their type/dimensional synthesis,kinematic/dynamic analyses,the error modeling and separation issues in PKMs are not studied adequately,which is one of the most important obstacles in its commercial applications widely.Taking a 3-PRS parallel manipulator as an example,this paper presents a separation method of source errors for 3-DOF parallel manipulator into the compensable and non-compensable errors effectively.The kinematic analysis of 3-PRS parallel manipulator leads to its six-dimension Jacobian matrix,which can be mapped into the Jacobian matrix of actuations and constraints,and then the compensable and non-compensable errors can be separated accordingly.The compensable errors can be compensated by the kinematic calibration,while the non-compensable errors may be adjusted by the manufacturing and assembling process.Followed by the influence of the latter,i.e.,the non-compensable errors,on the pose error of the moving platform through the sensitivity analysis with the aid of the Monte-Carlo method,meanwhile,the configurations of the manipulator are sought as the pose errors of the moving platform approaching their maximum.The compensable and non-compensable errors in limited-DOF parallel manipulators can be separated effectively by means of the Jacobian matrix of actuations and constraints,providing designers with an informative guideline to taking proper measures for enhancing the pose accuracy via component tolerancing and/or kinematic calibration,which can lay the foundation for the error distinguishment and compensation.展开更多
Based on a continuous piecewise-differentiable increasing functions vector, a class of robust nonlinear PID (RN-PID) controllers is proposed for setpoint control with uncertain Jacobian matrix. Globally asymptotic sta...Based on a continuous piecewise-differentiable increasing functions vector, a class of robust nonlinear PID (RN-PID) controllers is proposed for setpoint control with uncertain Jacobian matrix. Globally asymptotic stability is guaranteed and only position and joint velocity measurements are required. And stability problem arising from integral action and integrator windup, are consequently resolved. Furthermore, RN-PID controllers can be of effective alternative for anti-integrator-wind-up, the control performance would not be very bad in the presence of rough parameter tuning.展开更多
Parallel robot is used in many different fields nowadays, but the singularity of 3-RRUR parallel robot is more complicated, so a method to analyze the singularity of the 3-RRUR parallel robot is very necessary. First,...Parallel robot is used in many different fields nowadays, but the singularity of 3-RRUR parallel robot is more complicated, so a method to analyze the singularity of the 3-RRUR parallel robot is very necessary. First, the Jacobian matrix was built based on the differential transform method through the transfer matrixes between the poles. The connection between the position parameters and singularity condition was built through the analysis of the Jacobian matrix. Second, the effect on the singularity from the position parameters was analyzed, and then the singularity condition was confirmed. The effect on the singularity condition from position parameters was displayed by the curved surface charts to provide a basic method for the designing of the parallel robot. With this method, the singularity condition could be got when the length of each link is firmed, so it can be judged that if a group of parameters are appropriate or not, and the method also provides warrant for workspace and path planning of the parallel robot.展开更多
Due to the polarization effects of the Earth’s surface reflection and atmospheric particles’scattering,high-precision retrieval of atmospheric parameters from near-infrared satellite data requires accurate vector at...Due to the polarization effects of the Earth’s surface reflection and atmospheric particles’scattering,high-precision retrieval of atmospheric parameters from near-infrared satellite data requires accurate vector atmospheric radiative transfer simulations.This paper presents a near-infrared vector radiative transfer model based on the doubling and adding method.This new model utilizes approximate calculations of the atmospheric transmittance,reflection,and solar scattering radiance for a finitely thin atmospheric layer.To verify its accuracy,the results for four typical scenarios(single molecular layer with Rayleigh scattering,single aerosol layer scattering,multi-layer Rayleigh scattering,and true atmospheric with multi-layer molecular absorption,Rayleigh and aerosol scattering)were compared with benchmarks from a well-known model.The comparison revealed an excellent agreement between the results and the reference data,with accuracy within a few thousandths.Besides,to fulfill the retrieval algorithm,a numerical differentiation-based Jacobian calculation method is developed for the atmospheric and surface parameters.This is coupled with the adding and doubling process for the radiative transfer calculation.The Jacobian matrix produced by the new algorithm is evaluated by comparison with that from the perturbation method.The relative Jacobian matrix deviations between the two methods are within a few thousandths for carbon dioxide and less than 1.0×10-3%for aerosol optical depth.The two methods are consistent for surface albedo,with a deviation below 2.03×10-4%.All validation results suggest that the accuracy of the proposed radiative transfer model is suitable for inversion applications.This model exhibits the potential for simulating near-infrared measurements of greenhouse gas monitoring instruments.展开更多
The optimization inversion method based on derivatives is an important inversion technique in seismic data processing,where the key problem is how to compute the Jacobian matrix.The computation precision of the Jacobi...The optimization inversion method based on derivatives is an important inversion technique in seismic data processing,where the key problem is how to compute the Jacobian matrix.The computation precision of the Jacobian matrix directly influences the success of the optimization inversion method.Currently,all AVO(Amplitude Versus Offset) inversion techniques are based on approximate expressions of Zoeppritz equations to obtain derivatives.As a result,the computation precision and application range of these AVO inversions are restricted undesirably.In order to improve the computation precision and to extend the application range of AVO inversions,the partial derivative equation(Jacobian matrix equation(JME) for the P-and S-wave velocities inversion) is established with Zoeppritz equations,and the derivatives of each matrix entry with respect to Pand S-wave velocities are derived.By solving the JME,we obtain the partial derivatives of the seismic wave reflection coefficients(RCs) with respect to P-and S-wave velocities,respectively,which are then used to invert for P-and S-wave velocities.To better understand the behavior of the new method,we plot partial derivatives of the seismic wave reflection coefficients,analyze the characteristics of these curves,and present new understandings for the derivatives acquired from in-depth analysis.Because only a linear system of equations is solved in our method,the computation of Jacobian matrix is not only of high precision but also is fast and efficient.Finally,the theoretical foundation is established so that we can further study inversion problems involving layered structures(including those with large incident angle) and can further improve computational speed and precision.展开更多
Mathematical modeling of biochemical systems aims at improving the knowledge about complex regulatory networks. The experimental high-throughput measurement of levels of biochemical components, like metabolites and pr...Mathematical modeling of biochemical systems aims at improving the knowledge about complex regulatory networks. The experimental high-throughput measurement of levels of biochemical components, like metabolites and proteins, has become an integral part for characterization of biological systems. Yet, strategies of mathematical modeling to functionally integrate resulting data sets is still challenging. In plant biology, regulatory strategies that determine the metabolic output of metabolism as a response to changes in environmental conditions are hardly traceable by intuition. Mathematical modeling has been shown to be a promising approach to address such problems of plant-environment interaction promoting the comprehensive understanding of plant biochemistry and physiology. In this context, we recently published an inversely calculated solution for first-order partial derivatives, i.e. the Jacobian matrix, from experimental high-throughput data of a plant biochemical model system. Here, we present a biomathematical strategy, comprising 1) the inverse calculation of a biochemical Jacobian;2) the characterization of the associated eigenvalues and 3) the interpretation of the results with respect to biochemical regulation. Deriving the real parts of eigenvalues provides information about the stability of solutions of inverse calculations. We found that shifts of the eigenvalue real part distributions occur together with metabolic shifts induced by short-term and long-term exposure to low temperature. This indicates the suitability of mathematical Jacobian characterization for recognizing perturbations in the metabolic homeostasis of plant metabolism. Together with our previously published results on inverse Jacobian calculation this represents a comprehensive strategy of mathematical modeling for the analysis of complex biochemical systems and plant-environment interactions from the molecular to the ecosystems level.展开更多
基金supported by Tianjin Research Program of Application Foundation and Advanced Technology of China (Grant No.11JCZDJC22700)National Natural Science Foundation of China (GrantNo. 51075295,Grant No. 50675151)+1 种基金National High-tech Research and Development Program of China (863 Program,Grant No.2007AA042001)PhD Programs Foundation of Ministry of Education of China (Grant No. 20060056018)
文摘Parallel kinematic machines （PKMs） have the advantages of a compact structure,high stiffness,a low moving inertia,and a high load/weight ratio.PKMs have been intensively studied since the 1980s,and are still attracting much attention.Compared with extensive researches focus on their type/dimensional synthesis,kinematic/dynamic analyses,the error modeling and separation issues in PKMs are not studied adequately,which is one of the most important obstacles in its commercial applications widely.Taking a 3-PRS parallel manipulator as an example,this paper presents a separation method of source errors for 3-DOF parallel manipulator into the compensable and non-compensable errors effectively.The kinematic analysis of 3-PRS parallel manipulator leads to its six-dimension Jacobian matrix,which can be mapped into the Jacobian matrix of actuations and constraints,and then the compensable and non-compensable errors can be separated accordingly.The compensable errors can be compensated by the kinematic calibration,while the non-compensable errors may be adjusted by the manufacturing and assembling process.Followed by the influence of the latter,i.e.,the non-compensable errors,on the pose error of the moving platform through the sensitivity analysis with the aid of the Monte-Carlo method,meanwhile,the configurations of the manipulator are sought as the pose errors of the moving platform approaching their maximum.The compensable and non-compensable errors in limited-DOF parallel manipulators can be separated effectively by means of the Jacobian matrix of actuations and constraints,providing designers with an informative guideline to taking proper measures for enhancing the pose accuracy via component tolerancing and/or kinematic calibration,which can lay the foundation for the error distinguishment and compensation.
基金This work was supported by the Doctor Foundation of China(No.2003033306)
文摘Based on a continuous piecewise-differentiable increasing functions vector, a class of robust nonlinear PID (RN-PID) controllers is proposed for setpoint control with uncertain Jacobian matrix. Globally asymptotic stability is guaranteed and only position and joint velocity measurements are required. And stability problem arising from integral action and integrator windup, are consequently resolved. Furthermore, RN-PID controllers can be of effective alternative for anti-integrator-wind-up, the control performance would not be very bad in the presence of rough parameter tuning.
基金Supported by National High Technology Research and Development Program of China(2009AA04Z207)National Defense Basic Scientific Research Program of China(A2220080252)
文摘Parallel robot is used in many different fields nowadays, but the singularity of 3-RRUR parallel robot is more complicated, so a method to analyze the singularity of the 3-RRUR parallel robot is very necessary. First, the Jacobian matrix was built based on the differential transform method through the transfer matrixes between the poles. The connection between the position parameters and singularity condition was built through the analysis of the Jacobian matrix. Second, the effect on the singularity from the position parameters was analyzed, and then the singularity condition was confirmed. The effect on the singularity condition from position parameters was displayed by the curved surface charts to provide a basic method for the designing of the parallel robot. With this method, the singularity condition could be got when the length of each link is firmed, so it can be judged that if a group of parameters are appropriate or not, and the method also provides warrant for workspace and path planning of the parallel robot.
基金supported by the National Key R&D Program of China(Grant Nos.2018YFB0504900&2018YFB0504905)the National Natural Science Foundation of China(Grant No.41975034)the Special Fund for Scientific Research(Meteorology)in the Public Interest(Grant Nos.GYHY201506022&GYHY201506002)。
文摘Due to the polarization effects of the Earth’s surface reflection and atmospheric particles’scattering,high-precision retrieval of atmospheric parameters from near-infrared satellite data requires accurate vector atmospheric radiative transfer simulations.This paper presents a near-infrared vector radiative transfer model based on the doubling and adding method.This new model utilizes approximate calculations of the atmospheric transmittance,reflection,and solar scattering radiance for a finitely thin atmospheric layer.To verify its accuracy,the results for four typical scenarios(single molecular layer with Rayleigh scattering,single aerosol layer scattering,multi-layer Rayleigh scattering,and true atmospheric with multi-layer molecular absorption,Rayleigh and aerosol scattering)were compared with benchmarks from a well-known model.The comparison revealed an excellent agreement between the results and the reference data,with accuracy within a few thousandths.Besides,to fulfill the retrieval algorithm,a numerical differentiation-based Jacobian calculation method is developed for the atmospheric and surface parameters.This is coupled with the adding and doubling process for the radiative transfer calculation.The Jacobian matrix produced by the new algorithm is evaluated by comparison with that from the perturbation method.The relative Jacobian matrix deviations between the two methods are within a few thousandths for carbon dioxide and less than 1.0×10-3%for aerosol optical depth.The two methods are consistent for surface albedo,with a deviation below 2.03×10-4%.All validation results suggest that the accuracy of the proposed radiative transfer model is suitable for inversion applications.This model exhibits the potential for simulating near-infrared measurements of greenhouse gas monitoring instruments.
基金supported by Funding Project for Academic Human Resources Development in Institutions of Higher Learning (Grant No. PHR(20117145))National Natural Science Foundation of China (Grant No. 10705049)
文摘The optimization inversion method based on derivatives is an important inversion technique in seismic data processing,where the key problem is how to compute the Jacobian matrix.The computation precision of the Jacobian matrix directly influences the success of the optimization inversion method.Currently,all AVO(Amplitude Versus Offset) inversion techniques are based on approximate expressions of Zoeppritz equations to obtain derivatives.As a result,the computation precision and application range of these AVO inversions are restricted undesirably.In order to improve the computation precision and to extend the application range of AVO inversions,the partial derivative equation(Jacobian matrix equation(JME) for the P-and S-wave velocities inversion) is established with Zoeppritz equations,and the derivatives of each matrix entry with respect to Pand S-wave velocities are derived.By solving the JME,we obtain the partial derivatives of the seismic wave reflection coefficients(RCs) with respect to P-and S-wave velocities,respectively,which are then used to invert for P-and S-wave velocities.To better understand the behavior of the new method,we plot partial derivatives of the seismic wave reflection coefficients,analyze the characteristics of these curves,and present new understandings for the derivatives acquired from in-depth analysis.Because only a linear system of equations is solved in our method,the computation of Jacobian matrix is not only of high precision but also is fast and efficient.Finally,the theoretical foundation is established so that we can further study inversion problems involving layered structures(including those with large incident angle) and can further improve computational speed and precision.
文摘Mathematical modeling of biochemical systems aims at improving the knowledge about complex regulatory networks. The experimental high-throughput measurement of levels of biochemical components, like metabolites and proteins, has become an integral part for characterization of biological systems. Yet, strategies of mathematical modeling to functionally integrate resulting data sets is still challenging. In plant biology, regulatory strategies that determine the metabolic output of metabolism as a response to changes in environmental conditions are hardly traceable by intuition. Mathematical modeling has been shown to be a promising approach to address such problems of plant-environment interaction promoting the comprehensive understanding of plant biochemistry and physiology. In this context, we recently published an inversely calculated solution for first-order partial derivatives, i.e. the Jacobian matrix, from experimental high-throughput data of a plant biochemical model system. Here, we present a biomathematical strategy, comprising 1) the inverse calculation of a biochemical Jacobian;2) the characterization of the associated eigenvalues and 3) the interpretation of the results with respect to biochemical regulation. Deriving the real parts of eigenvalues provides information about the stability of solutions of inverse calculations. We found that shifts of the eigenvalue real part distributions occur together with metabolic shifts induced by short-term and long-term exposure to low temperature. This indicates the suitability of mathematical Jacobian characterization for recognizing perturbations in the metabolic homeostasis of plant metabolism. Together with our previously published results on inverse Jacobian calculation this represents a comprehensive strategy of mathematical modeling for the analysis of complex biochemical systems and plant-environment interactions from the molecular to the ecosystems level.
