Engineering topics

Houck, Jacob A.

Publications and source records attributed to Houck, Jacob A..

At least 19 records

NASA NTRS2015

Comparison of Flight Simulators Based on Human Motion Perception Metrics

In flight simulation, motion filters are used to transform aircraft motion into simulator motion. When looking for the best match between visual and inertial amplitude in a simulator, researchers have found that there is a range of inertial amplitudes, rather than a single inertial value, that is perceived by subjects as optimal. This zone, hereafter referred to as the optimal zone, seems to correlate to the perceptual coherence zones measured in flight simulators. However, no studies were found in which these two zones were compared. This study investigates the relation between the optimal and the coherence zone measurements within and between different simulators. Results show that for the sway axis, the optimal zone lies within the lower part of the coherence zone. In addition, it was found that, whereas the width of the coherence zone depends on the visual amplitude and frequency, the width of the optimal zone remains constant.

Valente Pais, Ana R.↗

NASA NTRS2013

Investigation of Control Inceptor Dynamics and Effect on Human Subject Performance

The control inceptor used in a vehicle simulation is an important part of adequately representing the dynamics of the vehicle. The inceptor characteristics are typically based on a second order spring mass damper system with damping, force gradient, breakout force, and natural frequency parameters. Changing these parameters can have a great effect on pilot control of the vehicle. A quasi transfer of training experiment was performed employing a high fidelity and a low fidelity control inceptor. A disturbance compensatory task was employed which involved a simple horizon line disturbed in roll by a sum of sinusoids presented in an out-the-window display. Vehicle dynamics were modeled as 1/s and 1/s2. The task was to maintain level flight. Twenty subjects were divided between the high and the low fidelity training groups. Each group was trained to a performance asymptote, and then transferred to the high fidelity simulation. RMS tracking error, a PSD analysis, and a workload analysis were performed to quantify the transfer of training effect. Quantitative results of the experiments show that there is no significant difference between the high and low fidelity training groups for 1/s plant dynamics. For 1/s2 plant dynamics there is a greater difference in tracking performance and PSD; and the subjects are less correlated with the input disturbance function

Stanco, Anthony A.↗

NASA NTRS2012

Algorithm for Simulating Atmospheric Turbulence and Aeroelastic Effects on Simulator Motion Systems

Atmospheric turbulence produces high frequency accelerations in aircraft, typically greater than the response to pilot input. Motion system equipped flight simulators must present cues representative of the aircraft response to turbulence in order to maintain the integrity of the simulation. Currently, turbulence motion cueing produced by flight simulator motion systems has been less than satisfactory because the turbulence profiles have been attenuated by the motion cueing algorithms. This report presents a new turbulence motion cueing algorithm, referred to as the augmented turbulence channel. Like the previous turbulence algorithms, the output of the channel only augments the vertical degree of freedom of motion. This algorithm employs a parallel aircraft model and an optional high bandwidth cueing filter. Simulation of aeroelastic effects is also an area where frequency content must be preserved by the cueing algorithm. The current aeroelastic implementation uses a similar secondary channel that supplements the primary motion cue. Two studies were conducted using the NASA Langley Visual Motion Simulator and Cockpit Motion Facility to evaluate the effect of the turbulence channel and aeroelastic model on pilot control input. Results indicate that the pilot is better correlated with the aircraft response, when the augmented channel is in place.

Ercole, Anthony V.↗

NASA NTRS2011

Relationship Between Optimal Gain and Coherence Zone in Flight Simulation

In motion simulation the inertial information generated by the motion platform is most of the times different from the visual information in the simulator displays. This occurs due to the physical limits of the motion platform. However, for small motions that are within the physical limits of the motion platform, one-to-one motion, i.e. visual information equal to inertial information, is possible. It has been shown in previous studies that one-to-one motion is often judged as too strong, causing researchers to lower the inertial amplitude. When trying to measure the optimal inertial gain for a visual amplitude, we found a zone of optimal gains instead of a single value. Such result seems related with the coherence zones that have been measured in flight simulation studies. However, the optimal gain results were never directly related with the coherence zones. In this study we investigated whether the optimal gain measurements are the same as the coherence zone measurements. We also try to infer if the results obtained from the two measurements can be used to differentiate between simulators with different configurations. An experiment was conducted at the NASA Langley Research Center which used both the Cockpit Motion Facility and the Visual Motion Simulator. The results show that the inertial gains obtained with the optimal gain are different than the ones obtained with the coherence zone measurements. The optimal gain is within the coherence zone.The point of mean optimal gain was lower and further away from the one-to-one line than the point of mean coherence. The zone width obtained for the coherence zone measurements was dependent on the visual amplitude and frequency. For the optimal gain, the zone width remained constant when the visual amplitude and frequency were varied. We found no effect of the simulator configuration in both the coherence zone and optimal gain measurements.

Gracio, Bruno Jorge Correia↗

NASA NTRS2011

A Transfer of Training Study of Control Loader Dynamics

The control inceptor used in a simulated vehicle is an important part in maintaining the fidelity of a simulation. The force feedback provided by the control inceptor gives the operator important cues to maintain adequate performance. The dynamics of a control inceptor are typically based on a second order spring mass damper system with damping, force gradient, breakout force, and natural frequency parameters. Changing these parameters can have a great effect on pilot or driver control of the vehicle. The neuromuscular system has a very important role in manipulating the control inceptor within a vehicle. Many studies by McRuer, Aponso, and Hess have dealt with modeling the neuromuscular system and quantifying the effects of a high fidelity control loader as compared to a low fidelity control loader. Humans are adaptive in nature and their control behavior changes based on different control loader dynamics. Humans will change their control behavior to maintain tracking bandwidth and minimize tracking error. This paper reports on a quasi-transfer of training experiment which was performed at the NASA Langley Research Center. The quasi transfer of training study used a high fidelity control loader and a low fidelity control loader. Subjects trained in both simulations and then were transferred to the high fidelity control loader simulation. The parameters for the high fidelity control loader were determined from the literature. The low fidelity control loader parameters were found through testing of a simple computer joystick. A disturbance compensatory task is employed. The compensatory task involves implementing a simple horizon out the window display. A disturbance consisting of a sum of sines is used. The task consists of the subject compensating for the disturbance on the roll angle of the aircraft. The vehicle dynamics are represented as 1/s and 1/s2. The subject will try to maintain level flight throughout the experiment. The subjects consist of non-pilots to remove any effects of pilot experience. First, this paper discusses the implementation of the disturbance compensation task. Second, the high and low fidelity parameters used within the experiment are presented. Finally, an explanation of results from the experiments is presented.

Cardullo, Frank M.↗

NASA NTRS2005

Motion Cueing Algorithm Development: New Motion Cueing Program Implementation and Tuning

A computer program has been developed for the purpose of driving the NASA Langley Research Center Visual Motion Simulator (VMS). This program includes two new motion cueing algorithms, the optimal algorithm and the nonlinear algorithm. A general description of the program is given along with a description and flowcharts for each cueing algorithm, and also descriptions and flowcharts for subroutines used with the algorithms. Common block variable listings and a program listing are also provided. The new cueing algorithms have a nonlinear gain algorithm implemented that scales each aircraft degree-of-freedom input with a third-order polynomial. A description of the nonlinear gain algorithm is given along with past tuning experience and procedures for tuning the gain coefficient sets for each degree-of-freedom to produce the desired piloted performance. This algorithm tuning will be needed when the nonlinear motion cueing algorithm is implemented on a new motion system in the Cockpit Motion Facility (CMF) at the NASA Langley Research Center.

Houck, Jacob A.↗

NASA NTRS2005

Motion Cueing Algorithm Development: Human-Centered Linear and Nonlinear Approaches

While the performance of flight simulator motion system hardware has advanced substantially, the development of the motion cueing algorithm, the software that transforms simulated aircraft dynamics into realizable motion commands, has not kept pace. Prior research identified viable features from two algorithms: the nonlinear "adaptive algorithm", and the "optimal algorithm" that incorporates human vestibular models. A novel approach to motion cueing, the "nonlinear algorithm" is introduced that combines features from both approaches. This algorithm is formulated by optimal control, and incorporates a new integrated perception model that includes both visual and vestibular sensation and the interaction between the stimuli. Using a time-varying control law, the matrix Riccati equation is updated in real time by a neurocomputing approach. Preliminary pilot testing resulted in the optimal algorithm incorporating a new otolith model, producing improved motion cues. The nonlinear algorithm vertical mode produced a motion cue with a time-varying washout, sustaining small cues for longer durations and washing out large cues more quickly compared to the optimal algorithm. The inclusion of the integrated perception model improved the responses to longitudinal and lateral cues. False cues observed with the NASA adaptive algorithm were absent. The neurocomputing approach was crucial in that the number of presentations of an input vector could be reduced to meet the real time requirement without degrading the quality of the motion cues.

Houck, Jacob A.↗

NASA NTRS2005

Motion Cueing Algorithm Development: Piloted Performance Testing of the Cueing Algorithms

The relative effectiveness in simulating aircraft maneuvers with both current and newly developed motion cueing algorithms was assessed with an eleven-subject piloted performance evaluation conducted on the NASA Langley Visual Motion Simulator (VMS). In addition to the current NASA adaptive algorithm, two new cueing algorithms were evaluated: the optimal algorithm and the nonlinear algorithm. The test maneuvers included a straight-in approach with a rotating wind vector, an offset approach with severe turbulence and an on/off lateral gust that occurs as the aircraft approaches the runway threshold, and a takeoff both with and without engine failure after liftoff. The maneuvers were executed with each cueing algorithm with added visual display delay conditions ranging from zero to 200 msec. Two methods, the quasi-objective NASA Task Load Index (TLX), and power spectral density analysis of pilot control, were used to assess pilot workload. Piloted performance parameters for the approach maneuvers, the vertical velocity upon touchdown and the runway touchdown position, were also analyzed but did not show any noticeable difference among the cueing algorithms. TLX analysis reveals, in most cases, less workload and variation among pilots with the nonlinear algorithm. Control input analysis shows pilot-induced oscillations on a straight-in approach were less prevalent compared to the optimal algorithm. The augmented turbulence cues increased workload on an offset approach that the pilots deemed more realistic compared to the NASA adaptive algorithm. The takeoff with engine failure showed the least roll activity for the nonlinear algorithm, with the least rudder pedal activity for the optimal algorithm.

Houck, Jacob A.↗

NASA NTRS2005

A Comprehensive Study of Three Delay Compensation Algorithms for Flight Simulators

This paper summarizes a comprehensive study of three predictors used for compensating the transport delay in a flight simulator; The McFarland, Adaptive and State Space Predictors. The paper presents proof that the stochastic approximation algorithm can achieve the best compensation among all four adaptive predictors, and intensively investigates the relationship between the state space predictor s compensation quality and its reference model. Piloted simulation tests show that the adaptive predictor and state space predictor can achieve better compensation of transport delay than the McFarland predictor.

Guo, Liwen↗

NASA NTRS2004

New Predictive Filters for Compensating the Transport Delay on a Flight Simulator

The problems of transport delay in a flight simulator, such as its sources and effects, are reviewed. Then their effects on a pilot-in-the-loop control system are investigated with simulations. Three current prominent delay compensators the lead/lag filter, McFarland filter, and the Sobiski/Cardullo filter were analyzed and compared. This paper introduces two novel delay compensation techniques an adaptive predictor using the Kalman estimator and a state space predictive filter using a reference aerodynamic model. Applications of these two new compensators on recorded data from the NASA Langley Research Center Visual Motion Simulator show that they achieve better compensation over the current ones.

Guo, Liwen↗

NASA NTRS2003

The Results of a Simulator Study to Determine the Effects on Pilot Performance of Two Different Motion Cueing Algorithms and Various Delays, Compensated and Uncompensated

A study was conducted employing the Visual Motion Simulator (VMS) at the NASA Langley Research Center, Hampton, Virginia. This study compared two motion cueing algorithms, the NASA adaptive algorithm and a new optimal control based algorithm. Also, the study included the effects of transport delays and the compensation thereof. The delay compensation algorithm employed is one developed by Richard McFarland at NASA Ames Research Center. This paper reports on the analyses of the results of analyzing the experimental data collected from preliminary simulation tests. This series of tests was conducted to evaluate the protocols and the methodology of data analysis in preparation for more comprehensive tests which will be conducted during the spring of 2003. Therefore only three pilots were used. Nevertheless some useful results were obtained. The experimental conditions involved three maneuvers; a straight-in approach with a rotating wind vector, an offset approach with turbulence and gust, and a takeoff with and without an engine failure shortly after liftoff. For each of the maneuvers the two motion conditions were combined with four delay conditions (0, 50, 100 & 200ms), with and without compensation.

Guo, Li-Wen↗

NASA NTRS2002

A Nonlinear, Human-Centered Approach to Motion Cueing with a Neurocomputing Solver

This paper discusses the continuation of research into the development of new motion cueing algorithms first reported in 1999. In this earlier work, two viable approaches to motion cueing were identified: the coordinated adaptive washout algorithm or 'adaptive algorithm', and the 'optimal algorithm'. In this study, a novel approach to motion cueing is discussed that would combine features of both algorithms. The new algorithm is formulated as a linear optimal control problem, incorporating improved vestibular models and an integrated visual-vestibular motion perception model previously reported. A control law is generated from the motion platform states, resulting in a set of nonlinear cueing filters. The time-varying control law requires the matrix Riccati equation to be solved in real time. Therefore, in order to meet the real time requirement, a neurocomputing approach is used to solve this computationally challenging problem. Single degree-of-freedom responses for the nonlinear algorithm were generated and compared to the adaptive and optimal algorithms. Results for the heave mode show the nonlinear algorithm producing a motion cue with a time-varying washout, sustaining small cues for a longer duration and washing out larger cues more quickly. The addition of the optokinetic influence from the integrated perception model was shown to improve the response to a surge input, producing a specific force response with no steady-state washout. Improved cues are also observed for responses to a sway input. Yaw mode responses reveal that the nonlinear algorithm improves the motion cues by reducing the magnitude of negative cues. The effectiveness of the nonlinear algorithm as compared to the adaptive and linear optimal algorithms will be evaluated on a motion platform, the NASA Langley Research Center Visual Motion Simulator (VMS), and ultimately the Cockpit Motion Facility (CMF) with a series of pilot controlled maneuvers. A proposed experimental procedure is discussed. The results of this evaluation will be used to assess motion cueing performance.

Telban, Robert J.↗

NASA NTRS2000

Motion Cueing Algorithm Development: Initial Investigation and Redesign of the Algorithms

In this project four motion cueing algorithms were initially investigated. The classical algorithm generated results with large distortion and delay and low magnitude. The NASA adaptive algorithm proved to be well tuned with satisfactory performance, while the UTIAS adaptive algorithm produced less desirable results. Modifications were made to the adaptive algorithms to reduce the magnitude of undesirable spikes. The optimal algorithm was found to have the potential for improved performance with further redesign. The center of simulator rotation was redefined. More terms were added to the cost function to enable more tuning flexibility. A new design approach using a Fortran/Matlab/Simulink setup was employed. A new semicircular canals model was incorporated in the algorithm. With these changes results show the optimal algorithm has some advantages over the NASA adaptive algorithm. Two general problems observed in the initial investigation required solutions. A nonlinear gain algorithm was developed that scales the aircraft inputs by a third-order polynomial, maximizing the motion cues while remaining within the operational limits of the motion system. A braking algorithm was developed to bring the simulator to a full stop at its motion limit and later release the brake to follow the cueing algorithm output.

Telban, Robert J.↗

NASA NTRS1997

Developments in Human Centered Cueing Algorithms for Control of Flight Simulator Motion Systems

The authors conducted further research with cueing algorithms for control of flight simulator motion systems. A variation of the so-called optimal algorithm was formulated using simulated aircraft angular velocity input as a basis. Models of the human vestibular sensation system, i.e. the semicircular canals and otoliths, are incorporated within the algorithm. Comparisons of angular velocity cueing responses showed a significant improvement over a formulation using angular acceleration input. Results also compared favorably with the coordinated adaptive washout algorithm, yielding similar results for angular velocity cues while eliminating false cues and reducing the tilt rate for longitudinal cues. These results were confirmed in piloted tests on the current motion system at NASA-Langley, the Visual Motion Simulator (VMS). Proposed future developments by the authors in cueing algorithms are revealed. The new motion system, the Cockpit Motion Facility (CMF), where the final evaluation of the cueing algorithms will be conducted, is also described.

Houck, Jacob A.↗

NASA NTRS1992

Effect of display parameters on pilots' ability to approach, flare and land

A workstation study is undertaken in which pilots conduct simulated landings via video images, and the effects are evaluated of field of view (FOV), magnification, resolution, update rate, and the use of aiding symbology. The simulation is conducted on the Advanced Real-time Simulation System with real-time controls, computer-generated imagery, and cockpit instrument displays. Five pilots fly 45 test runs with varying levels of FOV, update rate, aiding symbology, resolution, and magnification. Increased FOVs improve the runway streaming cues, and the pilots are shown to prefer unity magnification. Aiding symbology is shown to improve flare initiation and approach-heading variation, and the pilots prefer to use aiding symbology during the landing task. Update rate is also shown to have a critical effect on the pilots' ability to land the simulated aircraft.

Batson, Vernon M.↗

NASA NTRS1991

Development, simulation validation, and wind tunnel testing of a digital controller system for flutter suppression

Flutter suppression (FS) is one of the active control concepts being investigated by the AFW program. The design goal for FS control laws was to increase the passive flutter dynamic pressure by 30 percent. In order to meet this goal, the FS control laws had to be capable of suppressing both symmetric and antisymmetric flutter instabilities simultaneously. In addition, the FS control laws had to be practical and low-order, robust and capable of real time execution within the 200 hz. sampling time. The purpose here is to present an overview of the development, simulation validation, and wind tunnel testing of a digital controller system for flutter suppression.

Hoadley, Sherwood Tiffany↗

NASA NTRS1990

Hot-bench simulation of the active flexible wing wind-tunnel model

Two simulations, one batch and one real-time, of an aeroelastically-scaled wind-tunnel model were developed. The wind-tunnel model was a full-span, free-to-roll model of an advanced fighter concept. The batch simulation was used to generate and verify the real-time simulation and to test candidate control laws prior to implementation. The real-time simulation supported hot-bench testing of a digital controller, which was developed to actively control the elastic deformation of the wind-tunnel model. Time scaling was required for hot-bench testing. The wind-tunnel model, the mathematical models for the simulations, the techniques employed to reduce the hot-bench time-scale factors, and the verification procedures are described.

Buttrill, Carey S.↗

NASA NTRS1990

Delivery performance of conventional aircraft by terminal-area, time-based air traffic control: A real-time simulation evaluation

A description and results are presented of a study to measure the performance and reaction of airline flight crews, in a full workload DC-9 cockpit, flying in a real-time simulation of an air traffic control (ATC) concept called Traffic Intelligence for the Management of Efficient Runway-scheduling (TIMER). Experimental objectives were to verify earlier fast-time TIMER time-delivery precision results and obtain data for the validation or refinement of existing computer models of pilot/airborne performance. Experimental data indicated a runway threshold, interarrival-time-error standard deviation in the range of 10.4 to 14.1 seconds. Other real-time system performance parameters measured include approach speeds, response time to controller turn instructions, bank angles employed, and ATC controller message delivery-time errors.

Credeur, Leonard↗