A Design of Nonlinear Scaling and Nonlinear Optimal Motion Cueing Algorithm for Pilot's Station

Motion cueing algorithms (MCA) are often applied in the motion simulators. In this paper, a nonlinear optimal MCA, taking into account translational and rotational motions of a simulator within its physical limitation, is designed for the motion platform aiming to minimize human’s perception error in order to provide a high degree of fidelity. Indeed, the movement sensation center of most MCA is placed at the center of the upper platform, which may cause a certain error. Pilot’s station should be paid full attention to in the MCA. Apart from this, the scaling and limiting module plays an important role in optimizing the motion platform workspace and reducing false cues during motion reproduction. It should be used along within the washout filter to decrease the amplitude of the translational and rotational motion signals uniformly across all frequencies through the MCA. A nonlinear scaling method is designed to accurately duplicate motions with high realistic behavior and use the platform more efficiently without violating its physical limitations. The simulation experiment is verified in the longitudinal/pitch direction for motion simulator. The result implies that the proposed method can not only overcome the problem of the workspace limitations in the simulator motion reproduction and improve the realism of movement sensation, but also reduce the false cues to improve dynamic fidelity during the motion simulation process.

Development and Evaluation of a Threshold-Based Motion Cueing Algorithm

In this paper, a motion cueing algorithm (MCA) without a frequency divider is proposed, which aims to reproduce the longitudinal reference acceleration as far as possible via tilt coordination. Using a second-order rate limit, the human perception thresholds can directly be taken into account when parameterizing the MCA. The washout is compensated by tilt coordination and means of feedback from the translational acceleration. The proposed MCA is compared with the classical washout algorithm and the compensation MCA based on selected qualitative metrics and their workspace demand. In addition, a subjective study on the evaluation of the MCA was conducted. The results show that even high washout rates are not noticeable by the test subjects. Overall, the MCA was rated as very good.

Review of flight simulation fidelity requirements to help reduce ‘rotorcraft loss of control in-flight’ accident rates

This paper examines the fidelity requirements for flight simulators to improve training and address the problems associated with rotorcraft loss of control in-flight (LOC-I). To set the context, trends in rotorcraft accident statistics are presented. The data show that, despite recent safety initiatives, LOC-I rotorcraft accidents have been identified as a significant and growing contribution to accident rates. In the late 1990s, the fixed-wing commercial aircraft community faced a similar situation relating to upset prevention and recovery, and through a coordinated international effort, developed a focussed training programme to reduce accident rates. Lessons learned from the fixed-wing programme are presented to highlight how improved rotorcraft modelling and simulation tools are required to reduce rotorcraft accidents through higher quality, simulator-based training programmes. Relevant flight simulator certification standards are reviewed, with an emphasis on flight-model fidelity and vestibular motion cueing requirements. The findings from rotorcraft modelling and motion cueing research, that highlight relevant fidelity issues, are presented to identify areas for further activities to enhance the fidelity of simulators standards for use in LOC-I prevention training.

False cue influence on motion cue quality for 10 motion cueing algorithms

Motion simulators are becoming increasingly popular for many applications in which human sensation is important to replicate and optimize target motions. For the emulation of the perceived human acceleration, motion cueing algorithms (MCAs) have been proposed in the literature that mimics the motion sensation by a combination of actual acceleration and tilted gravity effects, termed g-force or specific force. However, their relative performance has not yet been analyzed. This paper reviews existing families of MCAs and compares their performance for a simple offline S-shaped planar test trajectory featuring only lateral acceleration. The comparison is carried out both numerically using two previously published objective measures, the “performance indicator” of Pouliot, Gosselin, and Nahon, and the “good criterion” of Schmidt, as well as subjectively by a preliminary passenger rating on a real motion platform—Robocoaster testbed. The results show that (a) the novel optimizing MCA group exploits more effectively the workspace of the motion platform than the traditional MCA group for reducing false cue with small scale error and shape errors, (b) path-dependent tuning of MCA parameters may improve motion sensation, (c) average subjective ratings can be made to correlate well with the “good criterion” when expanded with a penalty for false angular velocity cues, and (d) the scale error of specific force seems to play the most important role to the evaluation of test subject on the motion cue quality. However, still a strong variance in subjective ratings was observed, making further research necessary.