Communication Dans Un Congrès Année : 2026

Multi-Objective LQR-Based Optimization of Motion Cueing for Redundant Ski Simulator

Résumé

This paper presents an innovative multi-objective optimization system which optimizes Motion Cueing Algorithm (MCA) parameters for an eight-degree of-freedom (8-DoF) ski simulator that enhances rehabilitation and virtual sports training for disabled individuals. The system unites human vestibular models with Linear Quadratic Regulator (LQR)-based optimal control to achieve minimum perceptual differences between actual and simulated movements under the simulator’s mechanical limitation conditions. The system uses redundancy resolution to distribute motion between the 6-DoF hexapod and XY-table subsystem which enhances both workspace efficiency and motion precision. The proposed method demonstrates superior performance through simulation results which show it achieves 97% perceptual accuracy better than traditional washout filters. The system enables VR-based training and rehabilitation because it provides precise human sensation and redundant actuation capabilities.

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Dates et versions

hal-05541251 , version 1 (07-03-2026)

Identifiants

  • HAL Id : hal-05541251 , version 1

Citer

Taha Rhouda, Lotfi Beji, Ali Amouri. Multi-Objective LQR-Based Optimization of Motion Cueing for Redundant Ski Simulator. 6th IFSA Winter Conference on Automation, Robotics & Communications for Industry 4.0/5.0/6.0 (ARCI 2026), Feb 2026, Salzburg, Austria. ⟨hal-05541251⟩
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