Global Synchronous Optimized Predictive Control

Model predictive control, with its powerful performance and optimization potential, has attracted widespread attention and interest in academia. However, existing methods typically focus on the perspective of individual converter units, with limited exploration of the collaborative potential among converter clusters. In this work, we propose an enhanced predictive control technique to fill the above gap. In the proposed method, a global synchronized computation unit is introduced to enable pulse pattern coordination among the converter cluster. Subsequently, by reconstructing the cost function and incorporating an adaptive weight iteration mechanism, a refined trade-off between transient and steady-state performance is achieved within the control process. Experimental data confirm its effectiveness.

Authors

Institutions

Publication Details

Published
2025-06-05
DOI
https://doi.org/10.1109/precede63178.2025.11130979
Primary Topic
Advanced Control Systems Optimization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Global Synchronous Optimized Predictive Control

Zhenbin Zhang, Guangze Chen
Advanced Control Systems Optimization
article

Global Synchronous Optimized Predictive Control

Zhenbin Zhang, Guangze Chen
article en

Abstract

Model predictive control, with its powerful performance and optimization potential, has attracted widespread attention and interest in academia. However, existing methods typically focus on the perspective of individual converter units, with limited exploration of the collaborative potential among converter clusters. In this work, we propose an enhanced predictive control technique to fill the above gap. In the proposed method, a global synchronized computation unit is introduced to enable pulse pattern coordination among the converter cluster. Subsequently, by reconstructing the cost function and incorporating an adaptive weight iteration mechanism, a refined trade-off between transient and steady-state performance is achieved within the control process. Experimental data confirm its effectiveness.

Shandong University (CN)
Openalex Percentile: Top 72%
Advanced Control Systems Optimization
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.