Adaptive Horizon Model Predictive Control with Equivalent-Input-Disturbance for Vibration Suppression

This paper presents a vibration suppression method for two-inertia mechanical transmission systems, combining adaptive horizon model predictive control (AHMPC) with the equivalent-input-disturbance (EID) approach. First, conventional model predictive control (MPC) is extended to an adaptive horizon formulation to reduce computational cost while effectively attenuating vibrations. Second, a quadratic-programming-based method is designed to efficiently solve the AHMPC optimization problem. Third, the EID approach is integrated to compensate for external disturbances. Finally, simulation studies on a two-inertia system demonstrate the effectiveness of the proposed method in achieving significant vibration suppression.

Authors

Institutions

Publication Details

Journal
Journal of Advanced Computational Intelligence and Intelligent Informatics
Published
2026-01-19
DOI
https://doi.org/10.20965/jaciii.2026.p0176
Primary Topic
Control Systems in Engineering
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Adaptive Horizon Model Predictive Control with Equivalent-Input-Disturbance for Vibration Suppression

Ruoyu Jiang, Jinhua She, Xiang Yin, Seiichi Kawata
Journal of Advanced Computational Intelligence and Intelligent Informatics
Control Systems in Engineering
article

Adaptive Horizon Model Predictive Control with Equivalent-Input-Disturbance for Vibration Suppression

Ruoyu Jiang, Jinhua She, Xiang Yin, Seiichi Kawata
article en

Abstract

This paper presents a vibration suppression method for two-inertia mechanical transmission systems, combining adaptive horizon model predictive control (AHMPC) with the equivalent-input-disturbance (EID) approach. First, conventional model predictive control (MPC) is extended to an adaptive horizon formulation to reduce computational cost while effectively attenuating vibrations. Second, a quadratic-programming-based method is designed to efficiently solve the AHMPC optimization problem. Third, the EID approach is integrated to compensate for external disturbances. Finally, simulation studies on a two-inertia system demonstrate the effectiveness of the proposed method in achieving significant vibration suppression.

Journal of Advanced Computational Intelligence and Intelligent InformaticsVol. 30(1)
North China University of Technology (CN), Tokyo University of Technology (JP), China University of Geosciences (CN), Shandong Institute of Automation (CN)
Openalex Percentile: Top 84%
Control Systems in Engineering
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.