Building data platform with a graph change feed
US-12040911-B2 · Jul 16, 2024 · US
US2024255902A1 · US · A1
| Field | Value |
|---|---|
| Publication number | US-2024255902-A1 |
| Application number | US-202418430606-A |
| Country | US |
| Kind code | A1 |
| Filing date | Feb 1, 2024 |
| Priority date | Feb 16, 2023 |
| Publication date | Aug 1, 2024 |
| Grant date | — |
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An energy-saving strategy formulation method for a semi-automatic production line based on model predictive control is performed as follows. max-plus algebra model is constructed, based on which an optimization objective function with the WIP products as discrete elements and sleep start moment and sleep end moment of the automated device as control variables is established. A first unoptimized WIP product is substituted into the optimization objective function, and the optimization objective function is solved to obtain an optimal sequence, in which a first set of values is output as optimization result. Whether all WIP products have been optimized is determined, and if yes, an energy-saving strategy is generated and used to control the automated device, otherwise, the optimization result is treated as disturbance information to be incorporated into the modeling. An energy-saving strategy formulation system is also provided.
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What is claimed is: 1 . An energy-saving strategy formulation method for a semi-automatic production line based on model predictive control, comprising: (S 1 ) constructing a max-plus algebra model of the semi-automatic production line, wherein the semi-automatic production line comprises work-in-process (WIP) products and an automated device; and the max-plus algebra model is a production line model without controlling start and the stop of the automated device; (S 2 ) establishing, based on the max-plus algebra model, an optimization objective function with the WIP products as discrete elements, and a sleep start moment and a sleep end moment of the automated device as control variables; (S 3 ) substituting a first unoptimized WIP product among the WIP products into the optimization objective function, and solving the optimization objective function to obtain an optimal sequence comprising the sleep start moment and the sleep end moment of the automated device; and outputting a first set of values in the optimal sequence as an optimization result for the first unoptimized WIP product with respect to the automated device; (S 4 ) determining whether all of the WIP products in the semi-automatic production line have been optimized, if yes, proceeding to step (S 5 ); otherwise, treating the optimization result as a disturbance information, and returning to step (S 1 ) to incorporate the disturbance information into the construction of the max-plus algebra model; (S 5 ) generating an energy-saving strategy based on optimization results corresponding to all of the WIP products; and (S 6 ) controlling the automated device based on the energy-saving strategy. 2 . The energy-saving strategy formulation method of claim 1 , wherein in step (S 2 ), the optimization objective function satisfies the following formulas (1) to (4): min J = K 1 · J 1 + K 2 · J 2 ; ( 1 ) J 1 = ∑ i = 1 N p [ T l ( k + i ) - T s ( k + i | k ) ] ; ( 2 ) J 2 = - ∑ i = 1 N p ∑ s = 1 M { u k + i s - [ x s ( k + i - 1 | k ) + p s
using a predictor · CPC title
the criterion being a time optimal performance criterion · CPC title
Efficient use of energy, e.g. using compressed air or pressurized fluid as energy carrier · CPC title
in which a parameter or coefficient is automatically adjusted to optimise the performance · CPC title
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