Single-Loop Model-Free Predictive Control for Maximum Power Point Tracking of Permanent Magnet Direct Drive Wind Power System

In the implementation of the maximum power point tracking (MPPT) strategy for wind energy conversion systems, model predictive control (MPC) is a common control method. However, MPC is sensitive to parameters, and the long-term operation of wind energy conversion systems in harsh environments will inevitably lead to parameter changes. The paper first designs an extended state observer (ESO) to obtain the lumped disturbance required by the ultralocal model, and then designs a single-loop model-free predictive controller that is different from the conventional dual-loop control. This algorithm does not require precise parameters of the generator and mainly relies on the system's inputs and outputs to obtain its ultralocal model. Simulation results show that, compared with the MPC using the traditional mathematical model, the model-free predictive control proposed demonstrates better dynamic response characteristics and steady-state performance. after the system parameters change, and exhibits strong parameter robustness.

Authors

Institutions

Publication Details

Published
2025-03-21
DOI
https://doi.org/10.1109/icaace65325.2025.11019315
Primary Topic
Multilevel Inverters and Converters
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Single-Loop Model-Free Predictive Control for Maximum Power Point Tracking of Permanent Magnet Direct Drive Wind Power System

Shihong Gan, Tao Xiong
Multilevel Inverters and Converters
article

Single-Loop Model-Free Predictive Control for Maximum Power Point Tracking of Permanent Magnet Direct Drive Wind Power System

Shihong Gan, Tao Xiong
article en

Abstract

In the implementation of the maximum power point tracking (MPPT) strategy for wind energy conversion systems, model predictive control (MPC) is a common control method. However, MPC is sensitive to parameters, and the long-term operation of wind energy conversion systems in harsh environments will inevitably lead to parameter changes. The paper first designs an extended state observer (ESO) to obtain the lumped disturbance required by the ultralocal model, and then designs a single-loop model-free predictive controller that is different from the conventional dual-loop control. This algorithm does not require precise parameters of the generator and mainly relies on the system's inputs and outputs to obtain its ultralocal model. Simulation results show that, compared with the MPC using the traditional mathematical model, the model-free predictive control proposed demonstrates better dynamic response characteristics and steady-state performance. after the system parameters change, and exhibits strong parameter robustness.

Shanghai Maritime University (CN)
Affordable and clean energy
Openalex Percentile: Top 89%
Multilevel Inverters and Converters
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Single-Loop Model-Free Predictive Control for Maximum Power Point Tracking of Permanent Magnet Direct Drive Wind Power System — Shihong Gan, Tao Xiong · (2025) | TGRS Research Map | TGRS