Parameter identification problem is one of essential problem in order to model effectively experimental data by fractal interpolation function.In this paper,we first present an example to explain a relationship betwee...Parameter identification problem is one of essential problem in order to model effectively experimental data by fractal interpolation function.In this paper,we first present an example to explain a relationship between iteration procedure and fractal function.Then we discuss conditions that vertical scaling factors must obey in one typical case.展开更多
A novel maglev transportation system was proposed for large travel range ultra precision motion.The system consists of a levitation subsystem and a propulsion subsystem.During the propulsion subsystem driving the movi...A novel maglev transportation system was proposed for large travel range ultra precision motion.The system consists of a levitation subsystem and a propulsion subsystem.During the propulsion subsystem driving the moving platform along the guideway,the levitation subsystem uses six pairs of electromagnets to steadily suspend the moving platform over the guideway.The model of the levitation system,which is a typical nonlinear multi-input multi-output coupling system and has many inner nonlinear coupling characteristics,was deduced.For testifying the model,the levitation mechanism was firstly controlled by proportional-integral-differential(PID) control,and then a lot of input-output data were collected for model parameter identification.The least-square parameter identification method was used.The identification results prove that the model is feasible and suitable for the real system.展开更多
In this article, we propose a novel, multilevel, dynamic factor model, to determine endogenously clustered regions for the investigation of regional clustering and synchronization of provincial business fluctuations i...In this article, we propose a novel, multilevel, dynamic factor model, to determine endogenously clustered regions for the investigation of regional clustering and synchronization of provincial business fluctuations in China. The parameter identification and model estimation was conducted using the Markov Chain Monte Carlo method. We then conducted an empirical study of the provincial business fluctuations in China(31 Chinese provinces are considered except Hong Kong, Macao, and Taiwan due to the data unavailability), which were sampled from January 2000 to December 2015. Our results indicated that these provinces could be clustered into four regions: leading, coincident, lagging, and overshooting. In comparison with traditional geographical divisions, this novel clustering into four regions enabled the regional business cycle synchronization to be more accurately captured. Within the four regional clusters it was possible to identify substantial heterogeneities among regional business cycle fluctuations, especially during the periods of the 2008 financial crisis and the ‘four-trillion economic stimulus plan'.展开更多
A model to describe the hysteresis damper character of rubber material is presented in this paper. It consists of a parallel spring and damper, whose coefficients change with vibration frequencies. In order to acquire...A model to describe the hysteresis damper character of rubber material is presented in this paper. It consists of a parallel spring and damper, whose coefficients change with vibration frequencies. In order to acquire these relations, the force decomposition is carried out according to some sine vibration measurement data about nonlinear forces changing with deformations of the rubber material. The nonlinear force is decomposed into a spring force and a damper force, which are represented by a frequency-dependent spring and damper coefficient, respectively. Repeating this step for different measurements will give different coefficients corresponding to different frequencies. Then, application of a parameter identification method will provide the requested functions over frequency. Using those formulae, as an example, the dynamic character of a hollow shaft system supported by rubber rings is analyzed and the acceleration response curve in the centroid position is calculated. Comparisons with sine vibration experiments of the real system show a maximal inaccuracy of 8.8%. Application of this model and procedure can simplify the modeling and analysis of mechanical systems including rubber materials.展开更多
Artificial bee colony(ABC) algorithm is motivated by the intelligent behavior of honey bees when seeking a high quality food source. It has a relatively simple structure but good global optimization ability. In order ...Artificial bee colony(ABC) algorithm is motivated by the intelligent behavior of honey bees when seeking a high quality food source. It has a relatively simple structure but good global optimization ability. In order to balance its global search and local search abilities further, some improvements for the standard ABC algorithm are made in this study. Firstly, the local search mechanism of cuckoo search optimization(CS) is introduced into the onlooker bee phase to enhance its dedicated search; secondly, the scout bee phase is also modified by the chaotic search mechanism. The improved ABC algorithm is used to identify the parameters of chaotic systems, the identified results from the present algorithm are compared with those from other algorithms. Numerical simulations, including Lorenz system and a hyper chaotic system, illustrate the present algorithm is a powerful tool for parameter estimation with high accuracy and low deviations. It is not sensitive to artificial measurement noise even using limited input data.展开更多
This paper considers identification for the spatial variable coefficient of a vibrating string with Neumann boundary control from the measured boundary displacement. The reconstruction algorithm consists of two steps:...This paper considers identification for the spatial variable coefficient of a vibrating string with Neumann boundary control from the measured boundary displacement. The reconstruction algorithm consists of two steps: The first step is to recover the spectral data from the measured boundary displacement by showing that the system is spectral controllable; the second step is to reconstruct the coefficient from the recovered spectral data using the boundary control method, for which the required exact controllability is also verified.展开更多
文摘Parameter identification problem is one of essential problem in order to model effectively experimental data by fractal interpolation function.In this paper,we first present an example to explain a relationship between iteration procedure and fractal function.Then we discuss conditions that vertical scaling factors must obey in one typical case.
基金Projects(50735007,51005253) supported by the National Natural Science Foundation of ChinaProject(2007AA04Z344) supported by the National High-Tech Research and Development Program of China
文摘A novel maglev transportation system was proposed for large travel range ultra precision motion.The system consists of a levitation subsystem and a propulsion subsystem.During the propulsion subsystem driving the moving platform along the guideway,the levitation subsystem uses six pairs of electromagnets to steadily suspend the moving platform over the guideway.The model of the levitation system,which is a typical nonlinear multi-input multi-output coupling system and has many inner nonlinear coupling characteristics,was deduced.For testifying the model,the levitation mechanism was firstly controlled by proportional-integral-differential(PID) control,and then a lot of input-output data were collected for model parameter identification.The least-square parameter identification method was used.The identification results prove that the model is feasible and suitable for the real system.
基金Under the auspices of the National Natural Science Foundation of China(No.71371160)the Program for Changjiang Youth Scholars(No.Q2016131)the Program for New Century Excellent Talents in University(No.NCET-13-0509)
文摘In this article, we propose a novel, multilevel, dynamic factor model, to determine endogenously clustered regions for the investigation of regional clustering and synchronization of provincial business fluctuations in China. The parameter identification and model estimation was conducted using the Markov Chain Monte Carlo method. We then conducted an empirical study of the provincial business fluctuations in China(31 Chinese provinces are considered except Hong Kong, Macao, and Taiwan due to the data unavailability), which were sampled from January 2000 to December 2015. Our results indicated that these provinces could be clustered into four regions: leading, coincident, lagging, and overshooting. In comparison with traditional geographical divisions, this novel clustering into four regions enabled the regional business cycle synchronization to be more accurately captured. Within the four regional clusters it was possible to identify substantial heterogeneities among regional business cycle fluctuations, especially during the periods of the 2008 financial crisis and the ‘four-trillion economic stimulus plan'.
文摘A model to describe the hysteresis damper character of rubber material is presented in this paper. It consists of a parallel spring and damper, whose coefficients change with vibration frequencies. In order to acquire these relations, the force decomposition is carried out according to some sine vibration measurement data about nonlinear forces changing with deformations of the rubber material. The nonlinear force is decomposed into a spring force and a damper force, which are represented by a frequency-dependent spring and damper coefficient, respectively. Repeating this step for different measurements will give different coefficients corresponding to different frequencies. Then, application of a parameter identification method will provide the requested functions over frequency. Using those formulae, as an example, the dynamic character of a hollow shaft system supported by rubber rings is analyzed and the acceleration response curve in the centroid position is calculated. Comparisons with sine vibration experiments of the real system show a maximal inaccuracy of 8.8%. Application of this model and procedure can simplify the modeling and analysis of mechanical systems including rubber materials.
基金supported by the National Natural Science Foundation of China(Grant Nos.11172333&11272361)the Guangdong Province Natural Science Foundation(Grant No.2015A030313126)the Guangdong Province Science and Technology Program(Grant Nos.2014A020218004&2016A020223006)
文摘Artificial bee colony(ABC) algorithm is motivated by the intelligent behavior of honey bees when seeking a high quality food source. It has a relatively simple structure but good global optimization ability. In order to balance its global search and local search abilities further, some improvements for the standard ABC algorithm are made in this study. Firstly, the local search mechanism of cuckoo search optimization(CS) is introduced into the onlooker bee phase to enhance its dedicated search; secondly, the scout bee phase is also modified by the chaotic search mechanism. The improved ABC algorithm is used to identify the parameters of chaotic systems, the identified results from the present algorithm are compared with those from other algorithms. Numerical simulations, including Lorenz system and a hyper chaotic system, illustrate the present algorithm is a powerful tool for parameter estimation with high accuracy and low deviations. It is not sensitive to artificial measurement noise even using limited input data.
基金supported by the National Natural Science Foundation of China under Grant No.11326196the Doctoral Fund Program of Tianjin Normal University under Grant No.52XB1413
文摘This paper considers identification for the spatial variable coefficient of a vibrating string with Neumann boundary control from the measured boundary displacement. The reconstruction algorithm consists of two steps: The first step is to recover the spectral data from the measured boundary displacement by showing that the system is spectral controllable; the second step is to reconstruct the coefficient from the recovered spectral data using the boundary control method, for which the required exact controllability is also verified.
