Aiming at the contradiction between the depth control accuracy and the energy consumption of the self-sustaining intelligent buoy,a low energy consumption depth control method based on historical array for real-time g...Aiming at the contradiction between the depth control accuracy and the energy consumption of the self-sustaining intelligent buoy,a low energy consumption depth control method based on historical array for real-time geostrophic oceanography(Argo)data is proposed.As known from the buoy kinematic model,the volume of the external oil sac only depends on the density and temperature of seawater at hovering depth.Hence,we use historical Argo data to extract the fitting curves of density and temperature,and obtain the relationship between the hovering depth and the volume of the external oil sac.Genetic algorithm is used to carry out the optimal energy consumption motion planning for the depth control process,and the specific motion strategy of depth control process is obtained.Compared with dual closed-loop fuzzy PID control method and radial basis function(RBF)-PID method,the proposed method reduces energy consumption to 1/50 with the same accuracy.Finally,a hardware-in-the-loop simulation system was used to verify this method.When the error caused by fitting curves is not considered,the average error is 2.62 m,the energy consumption is 3.214×10^(4)J,and the error of energy consumption is only 0.65%.It shows the effectiveness and reliability of the method as well as the advantages of comprehensively considering the accuracy and energy consumption.展开更多
The net buoyancy of the deep-sea self-holding intelligent buoy(DSIB)will change with depth due to pressure hull deformation in the deep submergence process.The net buoyancy changes will affect the hovering performance...The net buoyancy of the deep-sea self-holding intelligent buoy(DSIB)will change with depth due to pressure hull deformation in the deep submergence process.The net buoyancy changes will affect the hovering performance of the DSIB.To make the DSIB have better resistance to the external disturbances caused by the net buoyancy and water resistance,a depth controller was designed to improve the depth positioning based on the active disturbance rejection control(ADRC).Firstly,a dynamic model was established based on the motion analysis of the DSIB.In addition,the extended state observer(ESO)and nonlinear state error feedback controller were designed based on the Lyapunov stability principle.Finally,semi-physical simulations for the depth control process were made by using the ADRC depth controller and traditional PID depth controller,respectively.The results of the semi-physical simulations indicate that the depth controller based on the ADRC can achieve the predefined depth control under the external disturbances.Compared with the traditional PID depth controller,the overshoot of the ADRC depth controller is 1.74%,and the depth error is within 0.5%.It not only has a better control capability to restrain the overshoot and shock caused by the external disturbances,but also can improve intelligence of the DSIB under the depth tracking task.展开更多
基金Qingdao Entrepreneurship and Innovation Leading Researchers Program(No.19-3-2-40-zhc)Key Research and Development Program of Shandong Province(Nos.2019GHY112072,2019GHY112051)Project Supported by State Key Laboratory of Precision Measuring Technology and Instruments(No.pilab1906).
文摘Aiming at the contradiction between the depth control accuracy and the energy consumption of the self-sustaining intelligent buoy,a low energy consumption depth control method based on historical array for real-time geostrophic oceanography(Argo)data is proposed.As known from the buoy kinematic model,the volume of the external oil sac only depends on the density and temperature of seawater at hovering depth.Hence,we use historical Argo data to extract the fitting curves of density and temperature,and obtain the relationship between the hovering depth and the volume of the external oil sac.Genetic algorithm is used to carry out the optimal energy consumption motion planning for the depth control process,and the specific motion strategy of depth control process is obtained.Compared with dual closed-loop fuzzy PID control method and radial basis function(RBF)-PID method,the proposed method reduces energy consumption to 1/50 with the same accuracy.Finally,a hardware-in-the-loop simulation system was used to verify this method.When the error caused by fitting curves is not considered,the average error is 2.62 m,the energy consumption is 3.214×10^(4)J,and the error of energy consumption is only 0.65%.It shows the effectiveness and reliability of the method as well as the advantages of comprehensively considering the accuracy and energy consumption.
基金Wenhai Program of Qingdao National Laboratory for Marine Science and Technology(No.ZR2016WH01)Tianjin Marine Economic Innovation and Development of Regional Demonstration Projects of State Oceanic Administration(No.BHSF2017-27)。
文摘The net buoyancy of the deep-sea self-holding intelligent buoy(DSIB)will change with depth due to pressure hull deformation in the deep submergence process.The net buoyancy changes will affect the hovering performance of the DSIB.To make the DSIB have better resistance to the external disturbances caused by the net buoyancy and water resistance,a depth controller was designed to improve the depth positioning based on the active disturbance rejection control(ADRC).Firstly,a dynamic model was established based on the motion analysis of the DSIB.In addition,the extended state observer(ESO)and nonlinear state error feedback controller were designed based on the Lyapunov stability principle.Finally,semi-physical simulations for the depth control process were made by using the ADRC depth controller and traditional PID depth controller,respectively.The results of the semi-physical simulations indicate that the depth controller based on the ADRC can achieve the predefined depth control under the external disturbances.Compared with the traditional PID depth controller,the overshoot of the ADRC depth controller is 1.74%,and the depth error is within 0.5%.It not only has a better control capability to restrain the overshoot and shock caused by the external disturbances,but also can improve intelligence of the DSIB under the depth tracking task.
