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Optimal boundary control of 1D colloid transport in a dead-end channel
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摘要
Diffusiophoresis occurs when colloids are placed in the non-uniform solute concentration. The colloids will be propelled in the direction of higher or lower concentration of the solute. In this paper, we consider the optimal boundary control of 1D colloid transport in a dead-end channel, which has a wide range of applications such as drug delivery, biology transport,oil recovery system and so on. Thus, we introduce a coupled system describing the colloid transport process and formulate an optimal control problem, in which the goal is to minimize colloid density distribution deviation between the computational one and the target at a pre-specified terminal time. To solve this optimal problem, we derive the gradient of the objective function based on the control parameterization method with respect to the decision parameters, which depends on the solution of the coupled system and the costate system. Finally, we propose an effective computational method and a gradient-based optimization algorithm to solve the optimal control problem numerically.
Diffusiophoresis occurs when colloids are placed in the non-uniform solute concentration. The colloids will be propelled in the direction of higher or lower concentration of the solute. In this paper, we consider the optimal boundary control of 1D colloid transport in a dead-end channel, which has a wide range of applications such as drug delivery, biology transport,oil recovery system and so on. Thus, we introduce a coupled system describing the colloid transport process and formulate an optimal control problem, in which the goal is to minimize colloid density distribution deviation between the computational one and the target at a pre-specified terminal time. To solve this optimal problem, we derive the gradient of the objective function based on the control parameterization method with respect to the decision parameters, which depends on the solution of the coupled system and the costate system. Finally, we propose an effective computational method and a gradient-based optimization algorithm to solve the optimal control problem numerically.
引文
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