A low-complexity explicit MPC controller for AFR control

Honek, Marek; Kvasnica, Michal; Szűcs, Alexander; Šimončič, Peter; Fikar, Miroslav; Rohal’-Ilkiv, Boris

doi:10.1016/j.conengprac.2015.05.009

Cited by 14 publications

(1 citation statement)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It was initially designed for slow response (i.e. long time constant) applications in process industry, but currently it is being used in high sampling rate applications owing to the development of advanced controllers with computational features (Honek, 2015; Leuer and Böcker 2013; Vazquez et al, 2014). MPC adjusts the manipulated variables according to the predicted response in such a way that the system output tracks the reference trajectory accurately (Lee, 2011).…”

Section: Introductionmentioning

confidence: 99%

Constrained model predictive control for an induction heating load

Nawaz

Saqib

Kashif

et al. 2018

Transactions of the Institute of Measurement and Control

View full text Add to dashboard Cite

This paper explores a model predictive control (MPC) strategy with constraints satisfaction for a high power induction heating load. The MPC predicts the state variables and future control sequence of the system in advance and achieves on-line-optimization with a reduced error. The state-space model of the system with a parallel resonant load is developed and then MPC is applied. The proposed approach controls the DC link current at the rectifier output and reactive component of the supply current. The DC current is used to regulate the power of the heating load and the reactive component of input current is kept at zero to attain the unity power factor. The results show that the proposed strategy regulates the power of the heating load, achieves unity power factor at input of the system and handles the variables within the defined constraints effectively.

show abstract