Extended Prediction Horizon Multi-objective FSMPC without Weighting Factors

Haotian Xie; Ralph Kennel; Fengxiang Wang; Marcelo Lobo Heldwein; Jose Rodriguez

doi:10.1109/PRECEDE57319.2023.10174576

Extended Prediction Horizon Multi-objective FSMPC without Weighting Factors

Haotian Xie^*, Ralph Kennel, Fengxiang Wang, Marcelo Lobo Heldwein, Jose Rodriguez

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Extended prediction horizon FS-MPC shows its merits of a low current harmonic distortion per switching frequency. However, the weighting factors are hard to be optimized in an extended prediction horizon FS-MPC with more involved control objectives. A multi-objective FS-MPC with a longer prediction horizon without the involvement of any weighting factors is proposed in this paper. The descriptions of control plant and FS-MPC with a prediction horizon of 3 are presented. The control objectives, torque, flux and switching frequency are optimized in the cost function. Therefore, there are two weighting factors to be optimized. To cope with the abovementioned issue, a ranking evaluation approach is proposed for weighting factor optimization in the proposed FSMPC method with an extended horizon to obtain two possible vectors, which are optimized in the next prediction horizon. The vector with a minimal ranking value is selected as the optimal. The simulation results of the proposed method on a pair of 2. 2kW induction machine drives are evaluated and compared.

Original language	English
Title of host publication	2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798350396867
ISBN (Print)	9798350396867
DOIs	https://doi.org/10.1109/PRECEDE57319.2023.10174576
State	Published - 2023
Event	2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023 - Wuhan, China Duration: 2023 → 2023

Publication series

Name	2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023

Conference

Conference	2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023
Country/Territory	China
City	Wuhan
Period	16/06/23 → 19/06/23

Bibliographical note

Funding Information:
ACKNOWLEDGEMENT J. Rodriguez acknowledges the support of ANID through projects FB0008, 1210208 and 1221293.

Publisher Copyright:
© 2023 IEEE.

ASJC Scopus subject areas

Control and Optimization
Modeling and Simulation
Energy Engineering and Power Technology
Electrical and Electronic Engineering
Mechanical Engineering
Safety, Risk, Reliability and Quality

Access to Document

10.1109/PRECEDE57319.2023.10174576

Cite this

Xie, H., Kennel, R., Wang, F., Heldwein, M. L., & Rodriguez, J. (2023). Extended Prediction Horizon Multi-objective FSMPC without Weighting Factors. In 2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023 (2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/PRECEDE57319.2023.10174576

Xie, Haotian ; Kennel, Ralph ; Wang, Fengxiang et al. / Extended Prediction Horizon Multi-objective FSMPC without Weighting Factors. 2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023).

@inproceedings{89ec29fda77d4b63af676def54ac3d50,

title = "Extended Prediction Horizon Multi-objective FSMPC without Weighting Factors",

abstract = "Extended prediction horizon FS-MPC shows its merits of a low current harmonic distortion per switching frequency. However, the weighting factors are hard to be optimized in an extended prediction horizon FS-MPC with more involved control objectives. A multi-objective FS-MPC with a longer prediction horizon without the involvement of any weighting factors is proposed in this paper. The descriptions of control plant and FS-MPC with a prediction horizon of 3 are presented. The control objectives, torque, flux and switching frequency are optimized in the cost function. Therefore, there are two weighting factors to be optimized. To cope with the abovementioned issue, a ranking evaluation approach is proposed for weighting factor optimization in the proposed FSMPC method with an extended horizon to obtain two possible vectors, which are optimized in the next prediction horizon. The vector with a minimal ranking value is selected as the optimal. The simulation results of the proposed method on a pair of 2. 2kW induction machine drives are evaluated and compared.",

keywords = "extended prediction horizon, model predictive control, multi-objective, weighting factor optimization",

author = "Haotian Xie and Ralph Kennel and Fengxiang Wang and Heldwein, {Marcelo Lobo} and Jose Rodriguez",

note = "Funding Information: ACKNOWLEDGEMENT J. Rodriguez acknowledges the support of ANID through projects FB0008, 1210208 and 1221293. Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023 ; Conference date: 16-06-2023 Through 19-06-2023",

year = "2023",

doi = "10.1109/PRECEDE57319.2023.10174576",

language = "English",

isbn = "9798350396867",

series = "2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023",

}

Xie, H, Kennel, R, Wang, F, Heldwein, ML & Rodriguez, J 2023, Extended Prediction Horizon Multi-objective FSMPC without Weighting Factors. in 2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023. 2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023, Institute of Electrical and Electronics Engineers Inc., 2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023, Wuhan, China, 16/06/23. https://doi.org/10.1109/PRECEDE57319.2023.10174576

Extended Prediction Horizon Multi-objective FSMPC without Weighting Factors. / Xie, Haotian; Kennel, Ralph; Wang, Fengxiang et al.
2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Extended Prediction Horizon Multi-objective FSMPC without Weighting Factors

AU - Xie, Haotian

AU - Kennel, Ralph

AU - Wang, Fengxiang

AU - Heldwein, Marcelo Lobo

AU - Rodriguez, Jose

PY - 2023

Y1 - 2023

N2 - Extended prediction horizon FS-MPC shows its merits of a low current harmonic distortion per switching frequency. However, the weighting factors are hard to be optimized in an extended prediction horizon FS-MPC with more involved control objectives. A multi-objective FS-MPC with a longer prediction horizon without the involvement of any weighting factors is proposed in this paper. The descriptions of control plant and FS-MPC with a prediction horizon of 3 are presented. The control objectives, torque, flux and switching frequency are optimized in the cost function. Therefore, there are two weighting factors to be optimized. To cope with the abovementioned issue, a ranking evaluation approach is proposed for weighting factor optimization in the proposed FSMPC method with an extended horizon to obtain two possible vectors, which are optimized in the next prediction horizon. The vector with a minimal ranking value is selected as the optimal. The simulation results of the proposed method on a pair of 2. 2kW induction machine drives are evaluated and compared.

AB - Extended prediction horizon FS-MPC shows its merits of a low current harmonic distortion per switching frequency. However, the weighting factors are hard to be optimized in an extended prediction horizon FS-MPC with more involved control objectives. A multi-objective FS-MPC with a longer prediction horizon without the involvement of any weighting factors is proposed in this paper. The descriptions of control plant and FS-MPC with a prediction horizon of 3 are presented. The control objectives, torque, flux and switching frequency are optimized in the cost function. Therefore, there are two weighting factors to be optimized. To cope with the abovementioned issue, a ranking evaluation approach is proposed for weighting factor optimization in the proposed FSMPC method with an extended horizon to obtain two possible vectors, which are optimized in the next prediction horizon. The vector with a minimal ranking value is selected as the optimal. The simulation results of the proposed method on a pair of 2. 2kW induction machine drives are evaluated and compared.

KW - extended prediction horizon

KW - model predictive control

KW - multi-objective

KW - weighting factor optimization

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DO - 10.1109/PRECEDE57319.2023.10174576

M3 - Conference contribution

AN - SCOPUS:85166239149

SN - 9798350396867

T3 - 2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023

BT - 2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023

Y2 - 16 June 2023 through 19 June 2023

ER -

Xie H, Kennel R, Wang F, Heldwein ML, Rodriguez J. Extended Prediction Horizon Multi-objective FSMPC without Weighting Factors. In 2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023. Institute of Electrical and Electronics Engineers Inc. 2023. (2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023). doi: 10.1109/PRECEDE57319.2023.10174576

Extended Prediction Horizon Multi-objective FSMPC without Weighting Factors

Abstract

Publication series

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Bibliographical note

ASJC Scopus subject areas

Access to Document

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