Interpolation-Based MCA for acceleration rendering

Martin Soyer (1) , Sorin Olaru (1) , Zhou Fang (2) , Didier Wautier (2) , Kemeny Andras (2)

1 L2S - Laboratoire des signaux et systèmes
2 Technocentre Renault [Guyancourt]

This paper deals with control design of high performance driving simulator Motion Cueing Algorithms (MCA). The highly constraint environment used by manufacturers to simulate driving experience implies a smart exploitation of the workspace and actuators in order to improve the acceleration feelings rendering to the driver. Since the two past decades, optimization-based motion cueing algorithms have been developed in this purpose, particularly, the Model Predictive Control (MPC) framework provides the handling of constraints applied to the system to find an optimal control action. However, the design of MPC-based MCA is a difficult task due to the theoretical and practical requirements such as stability and recursive feasibility guarantees. This contribution is a preliminary study of the application of a novel optimization-based control technique for MCA called Interpolation-Based Control (IBC). Recently developed, IBC showed similar performance as MPC for regulation problems by decreasing the computation time. In this paper, an extension of IBC to the tracking problem is studied for motion cueing.

Keywords: Model Predictive Control; Interpolation-Based Control; Motion Cueing Algorithm; Optimization

Domains: Automatic

Martin Soyer, Sorin Olaru, Zhou Fang, Didier Wautier, Kemeny Andras. Interpolation-Based MCA for acceleration rendering. Driving Simulation & Virtual Reality Conference & Exhibition, Sep 2020, Antibes, France. ⟨hal-03110450⟩