Six-DoF Stewart Platform Motion Simulator Control using Switchable Model Predictive Control

TL;DR

This work tackles the challenge of high-fidelity motion cueing for a 6-DoF Stewart platform under UPRT conditions by introducing a Switchable Model Predictive Control (S-MPC) based Motion Cueing Algorithm that combines a vestibular-aware predictive model with dual MPC schemes (with and without Terminal Conditions). A Supervisory Controller and Switch Mixer dynamically select and smooth transitions between the two MPC controllers, governed by solution feasibility and tracking error, to maintain realistic motion within the simulator envelope. Stability is supported by a receding-horizon framework and Riccati-based analysis, while time complexity scales linearly with the prediction horizon $N_p$. Simulation results in MATLAB show that S-MPC outperforms both CWF and standard MPC in bumpy and horizontal-stall scenarios, achieving lower NAAD and AAS and enabling rapid, smooth transitions at envelope limits. The proposed approach offers a practical route to more accurate, robust motion cueing for flight simulators.

Abstract

Due to excellent mechanism characteristics of high rigidity, maneuverability and strength-to-weight ratio, 6 Degree-of-Freedom (DoF) Stewart structure is widely adopted to construct flight simulator platforms for replicating motion feelings during training pilots. Unlike conventional serial link manipulator based mechanisms, Upset Prevention and Recovery Training (UPRT) in complex flight status is often accompanied by large speed and violent rate of change in angular velocity of the simulator. However, Classical Washout Filter (CWF) based Motion Cueing Algorithm (MCA) shows limitations in providing rapid response to drive motors to satisfy high accuracy performance requirements. This paper aims at exploiting Model Predictive Control (MPC) based MCA which is proved to be efficient in Hexapod-based motion simulators through controlling over limited linear workspace. With respect to uncertainties and control solution errors from the extraction of Terminal Constraints (COTC), this paper proposes a Switchable Model Predictive Control (S-MPC) based MCA under model adaptive architecture to mitigate the solution uncertainties and inaccuracies. It is verified that high accurate tracking is achievable using the MPC-based MCA with COTC within the simulator operating envelope. The proposed method provides optimal tracking solutions by switching to MPC based MCA without COTC outside the operating envelope. By demonstrating the UPRT with horizontal stall conditions following Average Absolute Scale(AAS) evaluation criteria, the proposed S-MPC based MCA outperforms MPC based MCA and SWF based MCA by 42.34% and 65.30%, respectively.

Figures (8)

• Figure 1: Stewart flight simulator motion platform.
• Figure 2: Overall MPC and S-MPC based MCA.
• Figure 3: Schematic diagram of coordination transfer between horizontal and vertical tilt of simulator.
• Figure 4: Geometric structure and reference coordinate system of simulator platform.
• Figure 5: S-MPC integrated MCA system diagram.