Disturbance‐rejection adjacent vector model predictive control strategy based on extended state observer for EV converter Article Swipe
Jianwei Zhang
,
Qiaosen Cao
,
Guangchen Liu
,
Marco Rivera
,
Patrick Wheeler
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1049/pel2.12807
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1049/pel2.12807
Conventional single‐vector model predictive control (MPC) can suffer from low control accuracy, while multi‐vector MPC is often criticized for its complexity and heavy computational burden. In order to address these issues, an adjacent vector‐based MPC is investigated in this paper for an electric vehicle battery charging and discharging converter. The voltage vector selection table based on the principle of using adjacent vectors has been designed and this reduces the number of iterations and thus the computational burden. A threshold is used in the adjacent vector‐based MPC to coordinate the use of the single and multi‐vector MPCs considering a balance between the control accuracy and computational burden. In addition, to enhance the robustness of MPC to parameter changes, an extended state observer for active disturbance rejection control has been used to derive the predictive model, and an adjacent vector‐based MPC using extended state observer is studied. The method does not need accurate system parameters. Instead, it only requires the system input and output measurements to calculate the predicted current. The robustness of the controller against the parameter mismatch is enhanced compared to alternative approaches and the experimental results verify the feasibility and effectiveness of the proposed strategy.
Related Topics
Concepts
Control theory (sociology)
Model predictive control
Robustness (evolution)
State vector
Computer science
Observer (physics)
Voltage
Vector control
State observer
Engineering
Control (management)
Artificial intelligence
Induction motor
Physics
Gene
Electrical engineering
Biochemistry
Nonlinear system
Classical mechanics
Quantum mechanics
Chemistry
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1049/pel2.12807
- OA Status
- gold
- References
- 24
- Related Works
- 10
- OpenAlex ID
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All OpenAlex metadata
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https://openalex.org/W4403566254Canonical identifier for this work in OpenAlex
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https://doi.org/10.1049/pel2.12807Digital Object Identifier
- Title
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Disturbance‐rejection adjacent vector model predictive control strategy based on extended state observer for EV converterWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
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2024Year of publication
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2024-10-19Full publication date if available
- Authors
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Jianwei Zhang, Qiaosen Cao, Guangchen Liu, Marco Rivera, Patrick WheelerList of authors in order
- Landing page
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https://doi.org/10.1049/pel2.12807Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
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https://doi.org/10.1049/pel2.12807Direct OA link when available
- Concepts
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Control theory (sociology), Model predictive control, Robustness (evolution), State vector, Computer science, Observer (physics), Voltage, Vector control, State observer, Engineering, Control (management), Artificial intelligence, Induction motor, Physics, Gene, Electrical engineering, Biochemistry, Nonlinear system, Classical mechanics, Quantum mechanics, ChemistryTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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