Model Of Human Pilot Research Articles

A Control Theoretical Adaptive Human Pilot Model: Theory and Experimental Validation

This article proposes an adaptive human pilot model that is able to mimic the crossover model in the presence of uncertainties. The proposed structure is based on the model reference adaptive control, and the adaptive laws are obtained using the Lyapunov–Krasovskii stability criteria. The model can be employed for human-in-the-loop stability and performance analyses incorporating different types of controllers and plant types. For validation purposes, an experimental setup is employed to collect data and a statistical analysis is conducted to measure the predictive power of the pilot model.

Modeling Fuzzy and Adaptive Human Behavior for Aircraft with Dynamic-Pitch-Control Envelope Cue

As one of the key issues in aviation safety, loss-of-control in the form of adverse aircraft-pilot couplings is attracting attention increasingly. Dynamic-pitch-control envelope shows to be a promising means to evaluate the loss-of-control related to pilot-induced oscillations. To mitigate this issue, this paper develops a human pilot model with the dynamic-pitch-control envelope cue. A key feature of the model is the capability to afford the characteristics of the pilot’s behavior through analyzing the cue of envelope boundaries in different areas. The fuzziness and adaption of the human are introduced into the model to describe the behavior of the human pilot. Fuzzy control logic is designed to reflect the fuzziness of the human’s response to the envelope cue. Time-varying parameters are adjusted to embody the adaptive characteristics of the human pilot to different regional envelope cues. Furthermore, three metrics methods, including error metric, envelope boundaries metric, and scalogram-based pilot-induced oscillation (PIO) metric, are proposed to design the dynamic-pitch-control envelope cues. The assessment results obtained by pilot–aircraft system simulation are compared with the pilot-in-the-loop flight experiment in-ground simulator to validate the effectiveness of the model. Simulation and experimental results show that the proposed human pilot model and envelope cue method can be applied to mitigate the loss-of-control events caused by the pilot–aircraft system oscillations.

An Adaptive Human Pilot Model for Adaptively Controlled Systems

Despite their success in handling uncertain dynamical systems that are prone to failure, adaptive controllers are observed to have unfavorable interactions with human pilots in certain applications. To alleviate this problem, we need to evaluate the safety and performance of adaptive controllers in the simulation environment using realistic pilot models before conducting flight tests. While many useful human pilot models exist in the literature, models that are adequate for the prediction of adaptive human-adaptive controller interactions are yet to be available. In this letter, we fill this gap by proposing an adaptive human pilot model suited for the prediction of human behavior in the loop with an adaptive controller. The model can serve as a valuable tool guiding the design of adaptive controllers so as to ensure smooth pilot-controller interactions.

A survey of human pilot models for study of Pilot-Induced Oscillation (PIO) in longitudinal aircraft motion

AbstractPilot-Induced Oscillation (PIO), although an old issue, still poses a significant threat to aviation safety. The introduction of new systems in modern aircraft modifies the human–machine interaction and makes it necessary for research to revisit the subject from time to time. Given the need of aircraft manufacturers to constantly perform PIO tests, this study analysed the feasibility of using three different computational pilot models (Tustin, Crossover and Precision) to simulate PIO conditions. Three aircraft models with different levels of propensity to PIO (original, low propensity and high propensity) were tested, as well as two pilot gain conditions (normal and high). Data were collected for a purely longitudinal synthetic task through simulations conducted in MATLAB®. PIO conditions were detect using a tuned PIO detection algorithm (ROVER). Data were analysed in terms of both whether the pilot models triggered a PIO condition and for how long the condition was sustained. The results indicated that the three pilot models only provoked PIO conditions when high gain inputs were applied. Additionally, Crossover was the only pilot model to trigger a PIO for the three aircraft models. There were also significant differences between the pilot models in the total PIO time, as the Tustin model typically sustained the oscillatory condition for longer.

Modeling multi-loop intelligent pilot control behavior for aircraft-pilot couplings analysis

Aircraft-pilot couplings (APCs) are one of the key factors that affect the flight safety of the modern aircraft. Among the several types of APCs, the nonlinear pilot induced oscillations caused by aircraft flight control system anomalies are extremely severe. In this paper, a multi-loop intelligent pilot model is presented for the analysis of the nonlinear pilot induced oscillations investigations. The multi-loop control tasks are introduced to define a typical multi-loop pilot modeling problem. The model is capable of describing the pilot's behavior during a multi-loop control task and analyzing the nonlinear pilot-induced oscillations when the flight control system is changed in different forms. Fuzzy control logic is designed to reflect the human pilot's behavior of making judgments. To be specific, the human pilot can change his/her control behavior adaptively when the aircraft flight control system falls into anomalies. Six cases of the abnormal flight control system are considered, and the control effects of the human pilot model are analyzed. The experimental results demonstrate that the human pilot can adjust the control strategy in different cases, which reflects the human pilot's adaptation to the changes of aircraft dynamics characteristics. Furthermore, it indicates that the human pilot model can obtain good control performance in tracking the command signal and can complete the task well facing the failures of the control system. Besides, the validity of the human pilot model is assessed by the scalogram-based PIO metric. The proposed pilot model can be applied in evaluating the aircraft loss-of-control events in the form of adverse aircraft-pilot couplings.

Mechanism Analysis of Smart Cue on Aircraft for Loss of Control Mitigation

This paper analyzes the mechanism of the smart inceptor on the aircraft, as a means to mitigate human-vehicle system loss-of-control. We divide the smart inceptor cue into three modes: the smart cue on the human pilot, the smart cue on the flight control system and the smart cue on both of them. The control mechanism of these three modes is developed and analyzed in depth. To evaluate the effect of the three modes, we utilize an intelligent human pilot model to establish the human-vehicle system with the smart inceptor and a scalogram-based pilot induced oscillation metric to predict the handling qualities of the three modes. This paper presents details of the cueing modes and the results of the prediction focused on effectiveness of these modes in preventing the pilots from entering a loss-of-control event. The simulation results indicate that the smart cue on both of them was the most effective method to mitigate the impact of the pilot-aircraft system oscillations for the given failure scenarios. It embodies the function of pilot-aircraft cooperation.

Modeling Human Pilot Behavior for Aircraft With a Smart Inceptor

This article presents a model of the human pilot for an aircraft with a smart inceptor, as a means to mitigate human–vehicle system loss–of–control. A key feature of the pilot model is the capability to reflect the interaction between the human–vehicle interface and the human pilot. The proposed human pilot model is primarily composed of a perception module, adaptation module, and execution module. The visual and tactile cues perceived from the human–vehicle interface including a smart inceptor are utilized to model the perception module. The adaptation module, including the central nervous system, is introduced to describe the adaptive behavior of the human pilot. In addition, the execution module contains the neuromuscular system of the human pilot so that the dynamics of the neuromuscular system and the smart inceptor are considered. The human pilot model is assessed by the time domain and wavelet–based analysis in comparison with the experiments of pilot–in–the–loop flight simulation. The simulation results indicate that the tracking results of the time histories given by this model are in good agreement with the behavioral characteristics of a test pilot. The potential applications of the human pilot model include the design of the smart inceptor and evaluation of aircraft loss–of–control events.

Prediction of nonlinear pilot-induced oscillation using an intelligent human pilot model

This paper proposes a method to predict nonlinear Pilot-Induced Oscillation (PIO) using an intelligent human pilot model. This method is based on a scalogram-based PIO metric, which uses wavelet transforms to analyze the nonlinear characteristics of a time-varying system. The intelligent human pilot model includes three modules: perception module, decision and adaptive module, and execution module. Intelligent and adaptive features, including a neural network receptor, fuzzy decision and adaptation, are also introduced into the human pilot model to describe the behavior of the human pilot accommodating the nonlinear events. Furthermore, an algorithm is proposed to describe the procedure of the PIO prediction method with nonlinear evaluation cases. The prediction results obtained by numerical simulation are compared with the assessments of flight test data to validate the utility of the method. The flight test data were generated in the evaluation of the Smart-Cue/Smart-Gain, which is capable of reducing the PIO tendencies considerably. The results show that the method can be applied to predict the nonlinear PIO events by human pilot model simulation.

A Fuzzy Human Pilot Model of Longitudinal Control for a Carrier Landing Task

Human pilot models are tightly dependent on the specific flight tasks. For a carrier landing task, the human pilot controls the aircraft glide path by the guidance information from the Fresnel lens optical landing system (FLOLS) during the aircraft approach to the carrier. This paper focuses on the modeling of the human pilot behavior of sensing and recognizing the guidance information from the Fresnel lens of the FLOLS in longitudinal motion. A fuzzy human pilot model is built based on a fuzzy logic control theory to simulate the human pilot behavior. The simulations of carrier landing are conducted to illustrate the advantages and effectiveness of the proposed fuzzy human pilot model.

Pilot modeling based on time-delay synthesis

A review of some human pilot models of the years 1970–1990 – the Kleinman–Baron–Levison optimal control model, the Davidson–Schmidt modified optimal control model, and the Hess optimal control model – has been presented from the perspective of a new model based on the optimal control synthesis of time-delay systems. In the first of the listed models, the ‘central nervous’ reaction of the pilot is naturally defined as a pure time delay in the measurement equation of the system. In the framework of the optimal control theory, the pilot’s behavior is modeled by linear quadratic regulator gain and Kalman–Bucy filter with a linear predictor. Starting from this optimal model of the 1970s, the other two models assumed the Padé approximation of the pure time delay, thus eliminating the linear predictor. In this article, the pure time delay of pilot reaction was reconsidered and divided, for convenience, into two equal parts: for the output measurement equation and for the input control. The pilot model problem has been first defined in the framework of rigorous time-delay synthesis and then solved by making reference to the control separation and duality principles. A closed-form expression of the solution is thereby obtained. The proposed model was then compared by numerical simulations with Kleinman and Hess consacrated models. The analysis of the results shows that this new pilot model is described by a simplified representation, instead denoting similar performance versus previous optimal models – which contains additional insertions as Kleinman–Baron predictor or Padé approximation, respectively. Finally, joint evaluation of the proposed model and Kleinman and Hess models with respect to the well-known Neal–Smith criterion confirms the consistency and viability of the employed strategy as a possible tool for pilot-induced oscillations phenomenon investigation.

Design of Probabilistic Pilot Model with Fuzzy Controller for Microburst Escape

Pilot should control the aircraft manually when encountering low altitude wind shear during takeoff and landing. For wind shear escape and flight safety research, an effective human pilot model together with wind shear and flight dynamics model should be built with high fidelity. A skill-based human pilot model was built which can describe pilots’ characteristics such as experiences, skills, emotions, reaction abilities, etc. A fuzzy controller was designed for lateral and longitudinal escape control in pilot model. Since single pilot could not represent a group of pilots’ control behavior, some of the model parameters were set to be stochastic, then the Monte Carlo method was adopted to obtain a numerical approximation of safety analysis results. With the probabilistic pilot model, escape strategies and safety analysis can be studied by simulation with high fidelity.

Safety Analysis of Aircraft Flying through Low Altitude Wind Shear

Low altitude microburst wind shear would do harm to aircrafts’ takeoff and landing. In order to analyze flight safety and advise better escape strategies, a mathematical model was built with high fidelity by a vortex ring based microburst model and a flight dynamics model with wind effects. A human pilot model which can describe characteristics of pilots such as skills, experiences, emotion, etc was embedded into the dynamics model. Since the key parameters of the microburst wind shear model and pilot model were set to be stochastic, the Monte Carlo method was adopted to obtain a numerical approximation of the probability density function of the minimum altitude and the F-factors for flight safety analysis.

PIO I-II tendencies. Part 2. Improving the pilot modeling

The study is conceived in two parts and aims to get some contributions to the problem of PIO aircraft susceptibility analysis. Part I, previously published in this journal, highlighted the main steps of deriving a complex model of human pilot. The current Part II of the paper considers a proper procedure of the human pilot mathematical model synthesis in order to analyze PIO II type susceptibility of a VTOL-type aircraft, related to the presence of position and rate-limited actuator. The mathematical tools are those of semi global stability theory developed in recent works.

Contributions of congruent pitch motion cue to human activity in manual control

The contribution of pitch motion cues to the performance of human pilots in compensatory tracking task are evaluated from pairs of uniquely planned experiments on a motion based research simulator, which allow separation of the visual responses from combined motion-visual responses. Analytical time series human pilot models of the least squares structure are evaluated from the input-output data and the results are discussed in terms of familiar parameters of pilot models and predictor operator. Beneficial contributions of pitch motion cues and subject differences are presented.

Contributions of Congruent Pitch Motion Cue to Human Activity in Manual Control

The contributions of pitch motion cue to the performance of human pilots in compensatory tracking task are evaluated by seperating the visual contributions from the combined motion visual contributions wherein the visual cue is congruent to the motion cue. Analytical human pilot models of the Least Squares (LS) structure are evaluated from the pilot input-output in uniquely planned motion based research simulator experiments. Beneficial contributions of the pitch motion cues in the form of lead and prediction are demonstrated.

Structural Model of the Adaptive Human Pilot

A compensatory tracking model of the human pilot is offered, which attempts to provide a more realistic representation of the human's signal processing structure than that which is exhibited by pilot models currently in use. Two features of the model distinguish it from other representations of the human pilot. First, proprioceptive information from the control stick or manipulator constitutes one of the major feedback paths in the model, providing feedback of vehicle output rate due to control activity. Implicit in this feedback loop is a model of the vehicle dynamics which is valid in and beyond the region of crossover. Second, error rate information is continuously derived and independently but intermittently controlled. An output-injected remnant model is offered and qualitatively justified on the basis of providing a measure of the effect of inaccuracies such as time variations in the pilot's internal model of the controlled-element dynamics. The data from experimental tracking tasks involving five different controlled-element dynamics and one nonideal viewing condition were matched with model-generated describing functions and remnant power spectral densities.

Analytic evaluation of display requirements for approach to landing

A computerized analysis procedure, based on a control theoretic model of the human pilot, is used to evaluate display requirements for longitudinal control in the landing approach. The display employed a digitally generated, perspective runway image with a superimposed artificial horizon for pitch indication. System performance measures are obtained for the approach phase of a light aircraft and a DC-8; predictions are made as to the effects of several display modifications. It is found that augmenting the basic display with glide slope reference bars and a velocity aim point yields adequate performance in calm air. Under moderate turbulence, the augmented display appears to be adequate for a DC-8 approach but not for a light aircraft.