In this paper, the admittance function between seafloor undulations and vertical gravity gradient anomalies was derived. Based on this admittance function, the bathymetry model of 1 minute resolution was predicted fro...In this paper, the admittance function between seafloor undulations and vertical gravity gradient anomalies was derived. Based on this admittance function, the bathymetry model of 1 minute resolution was predicted from vertical gravity gradient anomalies and ship soundings in the experimental area from the northwest Pacific. The accuracy of the model is evaluated using ship soundings and existing models, including ETOPO1, GEBCO, DTU10 and V15.1 from SIO. The model＇s STD is 69. 481m, comparable with V15.1 which is generally believed to have the highest accuracy.展开更多
According to the "theoretical admittance " and the "observation admittance" of the actual data,the theoretical value of effective elastic thickness in the study area was 10 km.Combining the gravity...According to the "theoretical admittance " and the "observation admittance" of the actual data,the theoretical value of effective elastic thickness in the study area was 10 km.Combining the gravity anomalies and vertical gravity gradient anomalies,the admittance function is used to construct the 1′×1′ bathymetry model over the Philippine Sea by using the adaptive weighting technique.It is found that the accuracy of the bathymetry model constructed is the highest when the ratio of inversion result of vertical gravity gradient anomalies and inversion result of gravity anomalies is 2∶3.At the same time,using multi-source gravity data to predict bathymetry could synthesize the superiority of gravity anomalies and vertical gravity gradient anomalies on the different seafloor topography,and the accuracy is better than bathymetry model that only used gravity anomalies or vertical gravity gradient anomalies.Taking the ship test data as the checking condition,the accuracy of predicting model is slightly lower than that of V18.1 model and improved by 27.17% and 39.02% respectively compared with the ETOPO1 model and the DTU10 model.Check points which the absolute value of the relative error of the predicting model is in the range of 5% accounted for 94.25% of the total.展开更多
In order to help the operator perform the human-robot collaboration task and optimize the task performance,an adaptive control method based on optimal admittance parameters is proposed.The overall control structure wi...In order to help the operator perform the human-robot collaboration task and optimize the task performance,an adaptive control method based on optimal admittance parameters is proposed.The overall control structure with the inner loop and outer loop is first established.The tasks of the inner loop and outer loop are robot control and task optimization,respectively.An inner-loop robot controller integrated with barrier Lyapunov function and radial basis function neural networks is then proposed,which makes the robot with unknown dynamics securely behave like a prescribed robot admittance model sensed by the operator.Subsequently,the optimal parameters of the robot admittance model are obtained in the outer loop to minimize the task tracking error and interaction force.The optimization problem of the robot admittance model is transformed into a linear quadratic regulator problem by constructing the human-robot collaboration system model.The model includes the unknown dynamics of the operator and the task performance details.To relax the requirement of the system model,the integral reinforcement learning is employed to solve the linear quadratic regulator problem.Besides,an auxiliary force is designed to help the operator complete the specific task better.Compared with the traditional control scheme,the security performance and interaction performance of the human-robot collaboration system are improved.The effectiveness of the proposed method is verified through two numerical simulations.In addition,a practical human-robot collaboration experiment is carried out to demonstrate the performance of the proposed method.展开更多
A framework was proposed to identify a comprehensive set of aerodynamic admittance functions for bridge decks. The contributions of the cross-spectra between longitudinal and vertical wind velocity components and betw...A framework was proposed to identify a comprehensive set of aerodynamic admittance functions for bridge decks. The contributions of the cross-spectra between longitudinal and vertical wind velocity components and between turbulence components and gust-induced forces were embedded in the identification procedure. To facilitate application of the identified functions in engineering practice, the concept of an equivalent aerodynamic admittance function was introduced and numerically validated. The equivalent aerodynamic admittance functions of a set of streamlined and bluff cross sections were identified experimentally in a wind tunnel. Buffeting analysis of a bridge deck was carried out and the response predicted using the identified aerodynamic admittance functions compared well with the measured response. In addition, a sensitivity analysis was performed to delineate the influence of aerodynamic and structural parameters on the buffeting response, thereby demonstrating the significance of the proposed identification framework.展开更多
基金supported by the Director Foundation of Institute of Seismology,China Earthquake Administration(IS201326125)the National Natural Science Foundation of China(41204019,41304003)
文摘In this paper, the admittance function between seafloor undulations and vertical gravity gradient anomalies was derived. Based on this admittance function, the bathymetry model of 1 minute resolution was predicted from vertical gravity gradient anomalies and ship soundings in the experimental area from the northwest Pacific. The accuracy of the model is evaluated using ship soundings and existing models, including ETOPO1, GEBCO, DTU10 and V15.1 from SIO. The model＇s STD is 69. 481m, comparable with V15.1 which is generally believed to have the highest accuracy.
基金The National Natural Science Foundation of China(41774021,41404020,41774018,41674082,41504018,41674026)The State Key Laboratory of Geo-Information Engineering(SKLGIE2016-M-3-2)The School Project(2017503902,2018222).
文摘According to the "theoretical admittance " and the "observation admittance" of the actual data,the theoretical value of effective elastic thickness in the study area was 10 km.Combining the gravity anomalies and vertical gravity gradient anomalies,the admittance function is used to construct the 1′×1′ bathymetry model over the Philippine Sea by using the adaptive weighting technique.It is found that the accuracy of the bathymetry model constructed is the highest when the ratio of inversion result of vertical gravity gradient anomalies and inversion result of gravity anomalies is 2∶3.At the same time,using multi-source gravity data to predict bathymetry could synthesize the superiority of gravity anomalies and vertical gravity gradient anomalies on the different seafloor topography,and the accuracy is better than bathymetry model that only used gravity anomalies or vertical gravity gradient anomalies.Taking the ship test data as the checking condition,the accuracy of predicting model is slightly lower than that of V18.1 model and improved by 27.17% and 39.02% respectively compared with the ETOPO1 model and the DTU10 model.Check points which the absolute value of the relative error of the predicting model is in the range of 5% accounted for 94.25% of the total.
基金the National Key R&D Program of China(No.2018YFB1308400)the Natural Science Foundation of Zhejiang Province(No.LY21F030018)。
文摘In order to help the operator perform the human-robot collaboration task and optimize the task performance,an adaptive control method based on optimal admittance parameters is proposed.The overall control structure with the inner loop and outer loop is first established.The tasks of the inner loop and outer loop are robot control and task optimization,respectively.An inner-loop robot controller integrated with barrier Lyapunov function and radial basis function neural networks is then proposed,which makes the robot with unknown dynamics securely behave like a prescribed robot admittance model sensed by the operator.Subsequently,the optimal parameters of the robot admittance model are obtained in the outer loop to minimize the task tracking error and interaction force.The optimization problem of the robot admittance model is transformed into a linear quadratic regulator problem by constructing the human-robot collaboration system model.The model includes the unknown dynamics of the operator and the task performance details.To relax the requirement of the system model,the integral reinforcement learning is employed to solve the linear quadratic regulator problem.Besides,an auxiliary force is designed to help the operator complete the specific task better.Compared with the traditional control scheme,the security performance and interaction performance of the human-robot collaboration system are improved.The effectiveness of the proposed method is verified through two numerical simulations.In addition,a practical human-robot collaboration experiment is carried out to demonstrate the performance of the proposed method.
基金supported by the National Natural Science Foundation of China(No.51778495)the National Key Research and Development Program of China(No.2017YFB1201204)。
文摘A framework was proposed to identify a comprehensive set of aerodynamic admittance functions for bridge decks. The contributions of the cross-spectra between longitudinal and vertical wind velocity components and between turbulence components and gust-induced forces were embedded in the identification procedure. To facilitate application of the identified functions in engineering practice, the concept of an equivalent aerodynamic admittance function was introduced and numerically validated. The equivalent aerodynamic admittance functions of a set of streamlined and bluff cross sections were identified experimentally in a wind tunnel. Buffeting analysis of a bridge deck was carried out and the response predicted using the identified aerodynamic admittance functions compared well with the measured response. In addition, a sensitivity analysis was performed to delineate the influence of aerodynamic and structural parameters on the buffeting response, thereby demonstrating the significance of the proposed identification framework.
