Adaptive Horizon Model Predictive Control with Equivalent-Input-Disturbance for Vibration Suppression
Year: 2026
Type: article
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.
Authors: Ruoyu Jiang, Xiang Yin, Seiichi Kawata, Jinhua She
Language: English
Subfield: Mechanical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
Funders: National Natural Science Foundation of China, China Postdoctoral Science Foundation, Natural Science Foundation of Hubei Province, Natural Science Foundation of Beijing Municipality, Higher Education Discipline Innovation Project, China University of Geosciences, Japan Society for the Promotion of Science
Awards: Postural clusters representing the voluntary movements that consist standing movements and their transition models, G26576258, G3711267653, G4108013643, G4414824831, G7447208349, G7998767293, G8360656225, Proposal of rehabilitation strategy for rhythmic normal gait to promote voluntary movement based on muscle synergy analysis
OpenAlex ID: W7124828344