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At least 73 records · Page 4

Pilot-aircraft system reponse to wind shear

The nonlinear aircraft motion and automatic control model is expanded to incorporate the human pilot into simulations of aircraft response to wind to wind shear. The human pilot is described by a constant gains lag filter. Two runs are carried out using pilot transfer functions. Fixed-stick, autopilot, and manned computer simulations are made with an aircraft having characteristics of a small commuter type aircraft flown through longitudinal winds measured by a Doppler radar beamed along the glide slope. Simulations are also made flying an aircraft through sinusoidal head wind and tail wind shears at the phugoid frequency to evaluate the response of manned aircraft in thunderstorm wind environments.

Turkel, B. S.↗

Characterization of Pilot Technique

Skilled pilots often use pulse control when controlling higher order (i.e. acceleration-command) vehicle dynamics. Pulsing does not produce a stick response that resembles what the human Crossover Model predicts. The Crossover Model (CM) assumes the pilot provides compensation necessary (lead or lag) such that the suite of display-human-vehicle approximates an integrator in the region of crossover frequency. However, it is shown that the CM does appear to drive the pilots pulsing behavior in a very predictable manner. Roughly speaking, the pilot generates pulses such that the area under the pulse (pulse amplitude multiplied by pulse width) is approximately equal to area under the hypothetical CM output. This can allow a pilot to employ constant amplitude pulsing so that only the pulse duration (width) is modulated a drastic simplification over the demands of continuous tracking. A pilot pulse model is developed, with which the parameters of the pilots internally-generated CM can be computed in real time for pilot monitoring and display compensation. It is also demonstrated that pursuit tracking may be activated when pulse control is employed.

rotorcraft↗

Reinforcement Learning with Autonomous Small Unmanned Aerial Vehicles in Cluttered Environments

We present ongoing work in the Autonomy Incubator at NASA Langley Research Center (LaRC) exploring the efficacy of a data set aggregation approach to reinforcement learning for small unmanned aerial vehicle (sUAV) flight in dense and cluttered environments with reactive obstacle avoidance. The goal is to learn an autonomous flight model using training experiences from a human piloting a sUAV around static obstacles. The training approach uses video data from a forward-facing camera that records the human pilot's flight. Various computer vision based features are extracted from the video relating to edge and gradient information. The recorded human-controlled inputs are used to train an autonomous control model that correlates the extracted feature vector to a yaw command. As part of the reinforcement learning approach, the autonomous control model is iteratively updated with feedback from a human agent who corrects undesired model output. This data driven approach to autonomous obstacle avoidance is explored for simulated forest environments furthering autonomous flight under the tree canopy research. This enables flight in previously inaccessible environments which are of interest to NASA researchers in Earth and Atmospheric sciences.

Tran, Loc↗

Optimal estimator model for human spatial orientation

A model is being developed to predict pilot dynamic spatial orientation in response to multisensory stimuli. Motion stimuli are first processed by dynamic models of the visual, vestibular, tactile, and proprioceptive sensors. Central nervous system function is then modeled as a steady-state Kalman filter which blends information from the various sensors to form an estimate of spatial orientation. Where necessary, this linear central estimator has been augmented with nonlinear elements to reflect more accurately some highly nonlinear human response characteristics. Computer implementation of the model has shown agreement with several important qualitative characteristics of human spatial orientation, and it is felt that with further modification and additional experimental data the model can be improved and extended. Possible means are described for extending the model to better represent the active pilot with varying skill and work load levels.

Borah, J.↗

A study of pilot modeling in multi-controller tasks

A modeling approach, which utilizes a matrix of transfer functions to describe the human pilot in multiple input, multiple output control situations, is studied. The approach used was to extend a well established scalar Wiener-Hopf minimization technique to the matrix case and then study, via a series of experiments, the data requirements when only finite record lengths are available. One of these experiments was a two-controller roll tracking experiment designed to force the pilot to use rudder in order to coordinate and reduce the effects of aileron yaw. One model was computed for the case where the signals used to generate the spectral matrix are error and bank angle while another model was computed for the case where error and yaw angle are the inputs. Several anomalies were observed to be present in the experimental data. These are defined by the descriptive terms roll up, break up, and roll down. Due to these algorithm induced anomalies, the frequency band over which reliable estimates of power spectra can be achieved is considerably less than predicted by the sampling theorem.

Whitbeck, R. F.↗

A model for the human's use of visual field cues in nap-of-the-Earth flight

A simple model is developed which describes the manner in which the human pilot may use visual field cues in controlling a vehicle in nap-of-the earth flight. The model is based upon the feedforward of information obtained from streamer patterns in the visual field to the inner-most loop of a multi-loop pilot/vehicle model. In this framework, the model is a logical extension of pursuit and preview models of the human operator which have appeared in the literature. Simulation and flight test data involving low-level helicopter flight tasks are applied to model development and validation.

Hess, R. A.↗

Cockpit control system

The purpose of this project is to provide a detail design for the cockpit control system of the Viper PFT. The statement of work for this project requires provisions for control of the ailerons, elevator, rudder, and elevator trim. The system should provide adjustment for pilot stature, rigging, and maintenance. MIL-STD-1472 is used as a model for human factors criterion. The system is designed to the pilot limit loading outlined in FAR part 23.397. The general philosophy behind this design is to provide a simple, reliable control system which will withstand the daily abuse that is experienced in the training environment without excessive cost or weight penalties.

Lesnewski, David↗

Pilot-aircraft system response to wind shear

The nonlinear aircraft motion and automatic control computer model of Frost and Reddy has been expanded to incorporate the human pilot into simulations of aircraft response to wind shear. Fixed-stick, autopilot, and manned computer simulations are made with an aircraft having characteristics of a Queen Air (small commuter-type aircraft) flown through longitudinal winds measured by a Doppler radar beamed along the glide slope during the SESAME '79 experiments in Oklahoma. Simulations are also made flying a model Boeing 727 through sinusoidal head wind to tail wind shears at the phugoid frequency to evaluate the response of manned aircraft in thunderstorm wind environments.

Turkel, B. S.↗

A method for generating numerical pilot opinion ratings using the optimal pilot model

A method for generating numerical pilot opinion ratings using the optimal pilot model is introduced. The method is contained in a rating hypothesis which states that the numerical rating which a human pilot assigns to a specific vehicle and task can be directly related to the numerical value of the index of performance resulting from the optimal pilot modeling procedure as applied to that vehicle and task. The hypothesis is tested using the data from four piloted simulations. The results indicate that the hypothesis is reasonable, but that the predictive capability of the method is a strong function of the accuracy of the pilot model itself. This accuracy is, in turn, dependent upon the parameters which define the optimal modeling problem. A procedure for specifying the parameters for the optimal pilot model in the absence of experimental data is suggested.

Hess, R. A.↗

Modified optimal control pilot model for computer-aided design and analysis

This paper presents the theoretical development of a modified optimal control pilot model based upon the optimal control model (OCM) of the human operator developed by Kleinman, Baron, and Levison. This model is input compatible with the OCM and retains other key aspects of the OCM, such as a linear quadratic solution for the pilot gains with inclusion of control rate in the cost function, a Kalman estimator, and the ability to account for attention allocation and perception threshold effects. An algorithm designed for each implementation in current dynamic systems analysis and design software is presented. Example results based upon the analysis of a tracking task using three basic dynamic systems are compared with measured results and with similar analyses performed with the OCM and two previously proposed simplified optimal pilot models. The pilot frequency responses and error statistics obtained with this modified optimal control model are shown to compare more favorably to the measured experimental results than the other previously proposed simplified models evaluated.

Davidson, John B.↗

Prediction of pilot-aircraft stability boundaries and performance contours

Control-theoretic pilot models can provide important new insights regarding the stability and performance characteristics of the pilot-aircraft system. Optimal-control pilot models can be formed for a wide range of flight conditions, suggesting that the human pilot can maintain stability if he adapts his control strategy to the aircraft's changing dynamics. Of particular concern is the effect of sub-optimal pilot adaptation as an aircraft transitions from low to high angle-of-attack during rapid maneuvering, as the changes in aircraft stability and control response can be extreme. This paper examines the effects of optimal and sub-optimal effort during a typical 'high-g' maneuver, and it introduces the concept of minimum-control effort (MCE) adaptation. Limited experimental results tend to support the MCE adaptation concept.

Stengel, R. F.↗

A linear stochastic model of the human operator

A linear stochastic model of the human operator is developed and applied to the problem of piloted control of an aircraft. The pilot and aircraft are modeled as linear time-invariant systems containing both process and measurement noise. The loop closure by the pilot is determined by formulating the problem as an optimal stochastic control problem. The solution to the optimal control problem yields not only the pilot's optimal control output which he uses to control the vehicle, but also the optimal combination of his observations of the vehicle states upon which the pilot bases his control. A method is presented so that, using experimental pilot vehicle data, the cost functional which is minimized in the optimal control problem will be numerically equal to the pilot rating that the pilot would associate with the given vehicle and task.

Durrett, J. C.↗

Modeling the pilot in visually controlled flight

The simplest model for a human operator is a gain with a time delay. However, there have been no comprehensive studies evaluating human control strategies in visually controlled flight. The results of preliminary studies on this topic are described. Human visually guided flight control is important both in low-level flight, where it predominates, and in higher-altitude flights, where instrument failure is always a potential danger. Two general approaches to this problem, one founded on high-order perceptual psychophysics and the other on control systems engineering, are described. Initial results show that the use of control engineering modeling techniques, together with a psychophysical analysis of information in the perspective scene, holds promise for capturing the manual control strategies used during visual flight.

Johnson, Walter W.↗

Modeling the pilot in visually controlled flight

The simplest model for a human operator is a gain with a time delay. However, there have been no comprehensive studies evaluating human control strategies in visually controlled flight. The results of preliminary studies on this topic are described. Human visually guided flight control is important both in low level flight, where it predominates, and in higher altitude flights, where instrument failure is always a potential danger. Two general approaches to this problem, one founded on high order perceptual psychophysics and the other on control systems engineering, are described. Initial results show that the use of control engineering modeling techniques, together with a psychophysical analysis of information in the perspective scene, holds promise for capturing the manual control strategies used during visual flight.

Johnson, Walter W.↗

Preliminary Exploration of Adaptive State Predictor Based Human Operator Modeling

Control-theoretic modeling of the human operator dynamic behavior in manual control tasks has a long and rich history. In the last two decades, there has been a renewed interest in modeling the human operator. There has also been significant work on techniques used to identify the pilot model of a given structure. The purpose of this research is to attempt to go beyond pilot identification based on collected experimental data and to develop a predictor of pilot behavior. An experiment was conducted to quantify the effects of changing aircraft dynamics on an operator s ability to track a signal in order to eventually model a pilot adapting to changing aircraft dynamics. A gradient descent estimator and a least squares estimator with exponential forgetting used these data to predict pilot stick input. The results indicate that individual pilot characteristics and vehicle dynamics did not affect the accuracy of either estimator method to estimate pilot stick input. These methods also were able to predict pilot stick input during changing aircraft dynamics and they may have the capability to detect a change in a subject due to workload, engagement, etc., or the effects of changes in vehicle dynamics on the pilot.

Trujillo, Anna C.↗

Adaptive State Predictor Based Human Operator Modeling on Longitudinal and Lateral Control

Control-theoretic modeling of the human operator dynamic behavior in manual control tasks has a long and rich history. In the last two decades, there has been a renewed interest in modeling the human operator. There has also been significant work on techniques used to identify the pilot model of a given structure. The purpose of this research is to attempt to go beyond pilot identification based on collected experimental data and to develop a predictor of pilot behavior. An experiment was conducted to categorize these interactions of the pilot with an adaptive controller compensating during control surface failures. A general linear in-parameter model structure is used to represent a pilot. Three different estimation methods are explored. A gradient descent estimator (GDE), a least squares estimator with exponential forgetting (LSEEF), and a least squares estimator with bounded gain forgetting (LSEBGF) used the experiment data to predict pilot stick input. Previous results have found that the GDE and LSEEF methods are fairly accurate in predicting longitudinal stick input from commanded pitch. This paper discusses the accuracy of each of the three methods - GDE, LSEEF, and LSEBGF - to predict both pilot longitudinal and lateral stick input from the flight director's commanded pitch and bank attitudes.

Trujillo, Anna C.↗

Some modern control techniques for human operator modeling and identification

Some recent results in quantitative modeling of the human operator are reviewed as well as a method for processing his input-output data. Modern control techniques are applied to the pilot operating in a dynamic compensatory tracking task. Trained pilots are known to behave in an optimal manner under fully stressed conditions. This has led to the development of an optimal control model of the human operator which takes his limitations into account. A rationale for determining the appropriate cost functions is determined. Experimental results indicate that the model can closely predict pilot performance in one- or two-axis tracking tasks. The model predicts pilot remnant (noise), error scores, and frequency response in both single-axis and multi-axis tracking tasks.

Shirley, R. S.↗