This paper addresses the source seeking problems for an autonomous underwater vehicle（AUV） with the estimated gradients. The AUV is embedded with multiple sensors, which are only able to detect the signal strengths ...This paper addresses the source seeking problems for an autonomous underwater vehicle（AUV） with the estimated gradients. The AUV is embedded with multiple sensors, which are only able to detect the signal strengths of the source with unknown distribution. To resolve this challenge,a sensor configuration is explicitly designed as a semicircle to estimate gradients of the signal field.Then, a controller is obtained via the estimated gradients to drive the AUV to approach the source.Moreover, an upper bound for the localization error is provided in terms of the radius of the semicircle and the signal distribution. Finally, the authors include a simulation example by applying the strategy to a Remote Environmental Monitoring Unit S（REMUS） for seeking the deepest point of a region of seabed in the South China Sea.展开更多
This paper presents two distributed stochastic source seeking controllers to navigate multiple vehicles to seek the signal source,using the measurements of the signal field at their own positions and information of th...This paper presents two distributed stochastic source seeking controllers to navigate multiple vehicles to seek the signal source,using the measurements of the signal field at their own positions and information of their neighbors.The first controller utilizes neighbors'measurements of the signal field and the second controller utilizes relative positions between neighbors.The effectiveness of the proposed two controllers is proved by the stochastic averaging theory.The convergence speed of the source seeking system can be calculated for the first controller and it is proved that the convergence speed under the second controller is not slower than that under the first controller.In particular,the distributed controllers are effective for both connected and unconnected graph.Numerical simulations are given to illustrate the effectiveness of the controllers.展开更多
Through the analysis on the migratory diffusion process of atmospheric pollutants,we proposed to seek atmospheric pollutant source with surface soil sample of data.Based on Gaussian plume model and deposition model,at...Through the analysis on the migratory diffusion process of atmospheric pollutants,we proposed to seek atmospheric pollutant source with surface soil sample of data.Based on Gaussian plume model and deposition model,atmospheric pollutants distribution model was deduced,with which a schema matching source seeking model was established.The model was used to seek the pollutant source by using the arsenic data in the surface soil sample of a city.展开更多
基金supported by the National Key Research and Development Program of China under Grant No.2016YFC0300801the National Natural Science Foundation of China under Grants Nos.41576101 and 41427806
文摘This paper addresses the source seeking problems for an autonomous underwater vehicle（AUV） with the estimated gradients. The AUV is embedded with multiple sensors, which are only able to detect the signal strengths of the source with unknown distribution. To resolve this challenge,a sensor configuration is explicitly designed as a semicircle to estimate gradients of the signal field.Then, a controller is obtained via the estimated gradients to drive the AUV to approach the source.Moreover, an upper bound for the localization error is provided in terms of the radius of the semicircle and the signal distribution. Finally, the authors include a simulation example by applying the strategy to a Remote Environmental Monitoring Unit S（REMUS） for seeking the deepest point of a region of seabed in the South China Sea.
基金supported by the National Natural Science Foundation of China under Grant No.61673284。
文摘This paper presents two distributed stochastic source seeking controllers to navigate multiple vehicles to seek the signal source,using the measurements of the signal field at their own positions and information of their neighbors.The first controller utilizes neighbors'measurements of the signal field and the second controller utilizes relative positions between neighbors.The effectiveness of the proposed two controllers is proved by the stochastic averaging theory.The convergence speed of the source seeking system can be calculated for the first controller and it is proved that the convergence speed under the second controller is not slower than that under the first controller.In particular,the distributed controllers are effective for both connected and unconnected graph.Numerical simulations are given to illustrate the effectiveness of the controllers.
文摘Through the analysis on the migratory diffusion process of atmospheric pollutants,we proposed to seek atmospheric pollutant source with surface soil sample of data.Based on Gaussian plume model and deposition model,atmospheric pollutants distribution model was deduced,with which a schema matching source seeking model was established.The model was used to seek the pollutant source by using the arsenic data in the surface soil sample of a city.
