Implementation of Control Structure for Steel Pickling Process using Model Predictive Controller

Lee, Ho Sub; Park, PooGyeon

doi:10.1016/j.ifacol.2022.07.522

Cited by 2 publications

(1 citation statement)

References 8 publications

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“…This necessitates exploring suitable control technique(s) for such systems. Model predictionled control (MPC) [13]- [18] has widely been employed in industries, as well as RPGRs-converter systems due to the possibility of control action modification at the intermediate level(s), online optimization, systematic method to assign specific weights to control inputs, simpler implementation, and capability to deal with multiple variables, constraints, and non-linearity [19]- [21]. Digital computing devices and interfacing hardware, lesser board-space requirement, supportive price (due to single-chip integrated multiple control functioning), and programming facility have popularized the digitalized control [22] of dc/dc converters.…”

Section: Introductionmentioning

confidence: 99%

Predictive load accommodation in a micro-grid

Laddha

Neeli

Vijayakumar

2023

IJPEDS

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This manuscript applies model prediction-based control (MPC) to accommodate the variable ac-natured load (AL) by optimally allocating the fuel cell (FC), battery, solar photovoltaic (SP) power in a four-port dc/dc converter (FPDDC). The presented work considers the FC, battery, SP, and AL at the first, second, third, and fourth ports of the FPDDC, respectively. The small signaled state-space representation of the FPDDC has been obtained through the improved cyclic averaged current. Then, to get the receding horizon-based MPC optimal control action, ∆u * [k] ; k = 0, 1, 2, 3, . . ., the above-mentioned model of the FPDDC is discretized. The ∆u * [k] has been obtained by formulating a performance index, Ja [k] based on an error minimization between the reference AL power demand, rpd [k] and the actual AL power, y [k]. The corresponding results have been obtained through the Simulink platform of the MATLAB. Further, the article takes sequential quadratic programming (SQP) into consideration to benchmark these solutions.

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