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首页> 外文期刊>IEEE Transactions on Control Systems Technology >Coupled Controls-Computational Fluids Approach for the Estimation of the Concentration From a Moving Gaseous Source in a 2-D Domain With a Lyapunov-Guided Sensing Aerial Vehicle
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Coupled Controls-Computational Fluids Approach for the Estimation of the Concentration From a Moving Gaseous Source in a 2-D Domain With a Lyapunov-Guided Sensing Aerial Vehicle

机译:用Lyapunov引导传感飞行器耦合控制-计算流体方法估算二维域中移动气态源的浓度

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摘要

The estimation of the gas concentration (process state) associated with an emitting stationary or moving source using a sensing aerial vehicle (SAV) is considered. The dispersion from such a gas source into the ambient atmosphere is representative of accidental or deliberate release of chemicals, or release of gases from the biological systems. Estimation of the concentration field provides a superior ability for source localization, assessment of possible adverse impacts, and eventual containment. The abstract and finite-dimensional approximation framework present couples theoretical estimation and control with computational fluid dynamics methods. The gas dispersion (process) model is based on the 2-D advection-diffusion equation with variable eddy diffusivities and ambient winds. The state estimator is a modified Luenberger observer with a collocated filter gain that is parameterized by the position of the SAV. The process-state (concentration) estimator is based on a 2-D adaptive, multigrid, multistep finite-volume method. The grid is adapted with local refinement and coarsening during the process-state estimation, to improve accuracy and efficiency. The 2-D motion dynamics of the SAV is incorporated into the spatial process and the SAV's guidance is directly linked to the performance of the state estimator. The computational model and the state estimator are coupled in the sense that grid refinement is affected by the SAV repositioning, and the guidance laws of the SAV are affected by grid refinement. Extensive numerical simulations serve to demonstrate the effectiveness of the coupled approach.
机译:考虑了使用感测飞行器(SAV)估算与发射固定源或移动源相关的气体浓度(过程状态)。从这种气体源到周围大气中的分散代表化学物质的意外或故意释放,或生物系统中气体的释放。浓度场的估算提供了出色的源定位,评估可能的不利影响以及最终控制的能力。当前的抽象和有限维近似框架将理论估计和控制与计算流体动力学方法结合在一起。气体扩散(过程)模型基于具有可变涡流和环境风的二维对流扩散方程。状态估计器是经过修改的Luenberger观测器,其并置滤波器增益由SAV的位置进行参数化。过程状态(浓度)估计器基于2D自适应,多网格,多步有限体积方法。在过程状态估计期间,对网格进行局部细化和粗化处理,以提高准确性和效率。 SAV的二维运动动力学被纳入空间过程,并且SAV的指导与状态估计器的性能直接相关。计算模型和状态估计器在网格细化受SAV重新定位影响,SAV的制导律受到网格细化影响的意义上耦合。大量的数值模拟证明了这种耦合方法的有效性。

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