A distributed model predictive control strategy for back-to-back converters
In recent years Model Predictive Control (MPC) has been successfully used for the control of power electronics converters with different topologies and for different applications. MPC offers many advantages over more traditional control techniques such as the ability to avoid cascaded control loops,...
| Main Authors: | , , , , , |
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| Format: | Article |
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Institute of Electrical and Electronics Engineers
2016
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| Online Access: | https://eprints.nottingham.ac.uk/35680/ |
| _version_ | 1848795136631242752 |
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| author | Tarisciotti, Luca Lo Calzo, Giovanni Gaeta, Alberto Zanchetta, Pericle Valencia, Felipe Saez, Doris |
| author_facet | Tarisciotti, Luca Lo Calzo, Giovanni Gaeta, Alberto Zanchetta, Pericle Valencia, Felipe Saez, Doris |
| author_sort | Tarisciotti, Luca |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | In recent years Model Predictive Control (MPC) has been successfully used for the control of power electronics converters with different topologies and for different applications. MPC offers many advantages over more traditional control techniques such as the ability to avoid cascaded control loops, easy inclusion of constraint and fast transient response. On the other hand, the controller computational burden increases exponentially with the system complexity and may result in an unfeasible realization on modern digital control boards. This paper proposes a novel Distributed Model Predictive Control, which is able to achieve the same performance of the classical Model Predictive Control whilst reducing the computational requirements of its implementation. The proposed control approach is tested on a AC/AC converter in a back-to-back configuration used for power flow management. Simulation results are provided and validated through experimental testing in several operating conditions. |
| first_indexed | 2025-11-14T19:27:18Z |
| format | Article |
| id | nottingham-35680 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:27:18Z |
| publishDate | 2016 |
| publisher | Institute of Electrical and Electronics Engineers |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-356802020-05-04T17:32:27Z https://eprints.nottingham.ac.uk/35680/ A distributed model predictive control strategy for back-to-back converters Tarisciotti, Luca Lo Calzo, Giovanni Gaeta, Alberto Zanchetta, Pericle Valencia, Felipe Saez, Doris In recent years Model Predictive Control (MPC) has been successfully used for the control of power electronics converters with different topologies and for different applications. MPC offers many advantages over more traditional control techniques such as the ability to avoid cascaded control loops, easy inclusion of constraint and fast transient response. On the other hand, the controller computational burden increases exponentially with the system complexity and may result in an unfeasible realization on modern digital control boards. This paper proposes a novel Distributed Model Predictive Control, which is able to achieve the same performance of the classical Model Predictive Control whilst reducing the computational requirements of its implementation. The proposed control approach is tested on a AC/AC converter in a back-to-back configuration used for power flow management. Simulation results are provided and validated through experimental testing in several operating conditions. Institute of Electrical and Electronics Engineers 2016-01-13 Article PeerReviewed Tarisciotti, Luca, Lo Calzo, Giovanni, Gaeta, Alberto, Zanchetta, Pericle, Valencia, Felipe and Saez, Doris (2016) A distributed model predictive control strategy for back-to-back converters. IEEE Transactions on Industrial Electronics . ISSN 1557-9948 (In Press) Predictive control Nonlinear control systems Back-to-back converters http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7403993 doi:10.1109/TIE.2016.2527693 doi:10.1109/TIE.2016.2527693 |
| spellingShingle | Predictive control Nonlinear control systems Back-to-back converters Tarisciotti, Luca Lo Calzo, Giovanni Gaeta, Alberto Zanchetta, Pericle Valencia, Felipe Saez, Doris A distributed model predictive control strategy for back-to-back converters |
| title | A distributed model predictive control strategy
for back-to-back converters |
| title_full | A distributed model predictive control strategy
for back-to-back converters |
| title_fullStr | A distributed model predictive control strategy
for back-to-back converters |
| title_full_unstemmed | A distributed model predictive control strategy
for back-to-back converters |
| title_short | A distributed model predictive control strategy
for back-to-back converters |
| title_sort | distributed model predictive control strategy
for back-to-back converters |
| topic | Predictive control Nonlinear control systems Back-to-back converters |
| url | https://eprints.nottingham.ac.uk/35680/ https://eprints.nottingham.ac.uk/35680/ https://eprints.nottingham.ac.uk/35680/ |