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Laguerre function-based model predictive control for multiple product inventory systems
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DOI：10.1080/23302674.2020.1846094.png)
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This paper describes Laguerre function-based model predictive control for a multiple-product inventory system. In periodic review inventory systems the control law is designed for replenishment orders to fill the stock. The orders for the products are issued such that the demand for the product is met and desired stock is maintained. The demand for the products is unknown prior and does not affect the system dynamics but the supplies and the arriving orders for their replenishment do affect the system. Model predictive control (MPC) is well known for constraint handling and Laguerre function based MPC is aimed to reduce the number of parameters in control thus enhancing computational efficiency. A set of discrete orthonormal basis function is introduced into the design to reduce the number of parameters. The control law for replenishment orders is derived to maintain desired stocks of the products in the inventory and to optimise the profit from the sale. Simulation results on a two product inventory system are shown for validation.
Keyword:
Inventory system
discrete system
model predictive control
Laguerre function
constraints
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