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Generalised model predictive controller design for A DC–DC non-inverting buck–boost converter optimised with a novel identification technique

Ghamari, Seyyed Morteza; Khavari, Fatemeh; Molaee, Hasan; Wheeler, Patrick

Generalised model predictive controller design for A DC–DC non-inverting buck–boost converter optimised with a novel identification technique Thumbnail


Authors

Seyyed Morteza Ghamari

Fatemeh Khavari

Hasan Molaee

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PATRICK WHEELER pat.wheeler@nottingham.ac.uk
Professor of Power Electronic Systems



Abstract

An on-line generalised model predictive control (GMPC) strategy is designed and optimised with a novel identification procedure in the presence of different disturbances. The principle of MPC is utilising a discrete-time model of a system to reach the control variables with a prediction over these values, which is followed by computing a cost function for the control aims. Non-inverting buck–boost converter is a non-minimum phase system based on its boost mode, which makes a challenging condition for designing a stable controller. The proposed control technique described in this paper removes the requirement for a system mathematical model adopting a black-box identification method which can decrease the computational burden. Numerous harmful disturbances can affect a DC–DC converter; thus, the GMPC scheme is used along with a novel improved exponential regressive least identification algorithm as an adaptive strategy for the controller to optimise the gains of the controller in an on-line way resulting in better disturbance rejection. A PID controller with particle swarm optimisation algorithm is designed for this converter to be compared with the GMPC controller. Finally, the efficiency of the GMPC is verified in various performances with experimental and simulation results.

Citation

Ghamari, S. M., Khavari, F., Molaee, H., & Wheeler, P. (2022). Generalised model predictive controller design for A DC–DC non-inverting buck–boost converter optimised with a novel identification technique. IET Power Electronics, https://doi.org/10.1049/pel2.12309

Journal Article Type Article
Acceptance Date Apr 26, 2022
Online Publication Date Jun 8, 2022
Publication Date Jun 8, 2022
Deposit Date Jul 7, 2022
Publicly Available Date Jul 7, 2022
Journal IET Power Electronics
Electronic ISSN 1755-4543
Publisher Institution of Engineering and Technology (IET)
Peer Reviewed Peer Reviewed
DOI https://doi.org/10.1049/pel2.12309
Keywords Electrical and Electronic Engineering
Public URL https://nottingham-repository.worktribe.com/output/8853753
Publisher URL https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/pel2.12309

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