In this paper, the online parameter identification problem of the mathematical model of an unmanned surface vehicle (USV) considering the characteristics of the actuator is studied. A data-driven mathematical model of...In this paper, the online parameter identification problem of the mathematical model of an unmanned surface vehicle (USV) considering the characteristics of the actuator is studied. A data-driven mathematical model of motion is very meaningful to realize trajectory prediction and adaptive motion control of the USV. An interactive identification algorithm (ESO–MILS, extended state observer–multi-innovation least squares) based on ESO is proposed. The robustness of online identification is improved by expanding the state observer to estimate the current disturbance without making artificial assumptions. Specifically, the three-degree-of-freedom dynamic equation of the double propeller propulsion USV is constructed. A linear model for online identification is derived by parameterization. Based on the least square criterion function, it is proved that the interactive identification method with disturbance estimation can improve the identification accuracy from the perspective of mathematical expectation. The extended state observer is designed to estimate the unknown disturbance in the model. The online interactive update improves the disturbance immunity of the identification algorithm. Finally, the effectiveness of the interactive identification algorithm is verified by simulation experiment and real ship experiment.展开更多
We find that a conserved mutation residue Glu to residue Asp （E303D）, which both have the same polar and charged properties, makes Kit2.1 protein lose its function. To understand the mechanism, we identify three int...We find that a conserved mutation residue Glu to residue Asp （E303D）, which both have the same polar and charged properties, makes Kit2.1 protein lose its function. To understand the mechanism, we identify three interactions which control the conformation change and maintain the function of the Kit2.1 protein by combining homology modeling and molecular dynamics with targeted molecular dynamics. We find that the E303D mutation weakens these interactions and results in the loss of the related function. Our data indicate that not only the amino residues but also the interactions determine the function of proteins.展开更多
基金supported by the National Natural Science Foundation of China(No.52271367).
文摘In this paper, the online parameter identification problem of the mathematical model of an unmanned surface vehicle (USV) considering the characteristics of the actuator is studied. A data-driven mathematical model of motion is very meaningful to realize trajectory prediction and adaptive motion control of the USV. An interactive identification algorithm (ESO–MILS, extended state observer–multi-innovation least squares) based on ESO is proposed. The robustness of online identification is improved by expanding the state observer to estimate the current disturbance without making artificial assumptions. Specifically, the three-degree-of-freedom dynamic equation of the double propeller propulsion USV is constructed. A linear model for online identification is derived by parameterization. Based on the least square criterion function, it is proved that the interactive identification method with disturbance estimation can improve the identification accuracy from the perspective of mathematical expectation. The extended state observer is designed to estimate the unknown disturbance in the model. The online interactive update improves the disturbance immunity of the identification algorithm. Finally, the effectiveness of the interactive identification algorithm is verified by simulation experiment and real ship experiment.
基金Supported by the National Natural Science Foundation of China under Grant Nos 11247010,11175055,11475053 and 11347017the Natural Science Foundation of Hebei Province under Grant Nos C2012202079 and C201400305
文摘We find that a conserved mutation residue Glu to residue Asp （E303D）, which both have the same polar and charged properties, makes Kit2.1 protein lose its function. To understand the mechanism, we identify three interactions which control the conformation change and maintain the function of the Kit2.1 protein by combining homology modeling and molecular dynamics with targeted molecular dynamics. We find that the E303D mutation weakens these interactions and results in the loss of the related function. Our data indicate that not only the amino residues but also the interactions determine the function of proteins.
