A Nonlinear Motion Cueing Algorithm With a Human Perception Model
The objective of a motion system, when used in conjunction with a visual system, is to stimulate the pilot so that he can perceive the required motion cues necessary to fly the simulator within the same performance and control activity as the aircraft. An example of a motion system is the six-degree-of-freedom hexapod shown in Figure E.l. Platform motion allows the pilot to react more quickly to simulated aircraft motion as compared to visual stimuli alone, thus enabling him to co1Tect (and reduce the magnitude) of any deviation sooner than having to wait for the information visually. Without motion cues the pilot's perception of the simulated vehicle motion is degraded and the aircraft response feels slower. The vehicle simulation structure for a motion system is shown in Figure E.2. The operator control inputs drive a mathematical model of the vehicle dynamics, generating the vehicle states. The desired motion cues and platform states are produced by passing the vehicle states through the motion cueing algorithm. The desired platform states are then transformed from degree-of-freedom space to actuator space, generating the desired commands to the six actuators. The actuator motion commands serve as input to the closed-loop platform dynamics, resulting in actual simulator motion. The motion cueing algorithm generates the desired motion cues that are constrained within the physical limits of the motion system. The magnitude of the cues is reduced by scaling and limiting the vehicle states. The duration of the cues is limited by a technique known as washout. Washout involves returning the platform state to a neutral position following the initial, or "onset" portion of a motion cue, thus "washing out" the resulting cue at levels below the pilot's perceptual threshold. This is accomplished by passing the vehicle state through a high-pass filter, removing long-duration (low-frequency) motion components. Figure E.3 shows the response of a washout filter to an acceleration ramp to step input. Early approaches to washout filtering used simple (first- and second-order) linear filters in which the ratio of onset to washout duration was fixed. Nonlinear approaches were later developed where this ratio varied with time. The otolith organs in the human vestibular system sense both acceleration and tilting of the pilot's head with respect to the gravity vector. Since the otoliths cannot discriminate between acceleration and tilt, this phenomenon, known as tilt coordination, can be used to advantage in motion simulation. For long-term specific force simulation, acceleration cues simulated by high-pass washout filters are augmented by tilting the motion platform at a rate below the pilot's perceptual threshold. This additional cue results from passing the vehicle acceleration through a low-pass filter to produce the desired long-duration tilt cue. Tilt coordination is implemented in a motion cueing algorithm by adding additional filters in the longitudinal (pitch/surge) and lateral (roll/sway) modes that produce the additional cues. For this reason four separate modes are implemented in a motion cueing alg01ithm: longitudinal, lateral, yaw, and heave.