Pilot Control Behavior Research Articles

Competency-based assessment of pilots’ manual flight performance during instrument flight training

A pilot's control behavior has a direct impact on aviation safety. To adapt to new flight training reforms, a competency-based assessment method is proposed in this paper. First, assessment scenarios, key competencies and observable behaviours were determined. Then, observable behavior assessment indexes were developed based on standard operating procedures and practical examination standards. Flight training data were analyzed based on curve similarity theory and a time series fast retrieval algorithm, and the assessment indexes were scored. The competency assessment method was established by quantifying “HOW MANY” and “HOW OFTEN” observable behaviors according to the assessment indexes score results. Finally, the fuzzy C-means clustering algorithm was used to classify the assessment values, and assessment results were obtained. A teardrop pattern procedure was used to test the reliability of the assessment method. The results indicate that the correlation coefficient between the model evaluation and the expert evaluation is 0.947 with a significance level of 0.01, reliably and objectively quantifying manual flight performance and improving the scientific nature of manual flight performance assessment methods. Flight training institutions can use this method to establish diverse assessment scenarios and formulate corresponding assessment indexes based on the characteristics of each pilot to reasonably evaluate the manual flight performance of pilot. Targeted training methods can then be adopted for pilot with different performance levels to improve their competency.

Between-Simulator Comparison of Motion-Filter Order and Break Frequency Effects on Manual Control

This paper investigates the interaction effects of motion filter order and break frequency on pilots’ manual control behavior and control performance using two simulators. Eighteen pilots performed the experiment in the Vertical Motion Simulator (VMS) at NASA Ames Research Center and 20 pilots in the SIMONA Research Simulator at Delft University of Technology. The experiment used a full-factorial design with three motion filter orders (first-, second-, and third-order) and two filter break frequencies (0.5 and ), in addition to reference no-motion and full-motion conditions. Key task variables, such as the quality of the motion and visual cues and the characteristics of the sidestick, were matched across both simulators. Overall, the expected effects of filter order and break frequency variations were found, with both increasing order and increasing break frequency causing pilots to use less motion feedback in their control strategy, resulting in lower tracking performance. Furthermore, across the wide range of filter orders tested in the experiment, the existing Sinacori–Schroeder motion fidelity criterion was found to be a good predictor of the interaction effects of both filter settings on pilot control behavior. For the same motion condition, there was a consistent offset in the results between simulators, due to the more high-gain control strategy adopted by a number of the VMS pilots. Still, the observed relative trends in pilot control behavior and performance between motion conditions were equivalent in both simulators and thus accurately replicated.

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.

Pilot Control Modeling With Stochastic Periodical Discrete Movement

This paper proposes a novel pilot control model which reflects the following three characteristics of the pilot control behavior: stochastic, periodical, and discrete movement. The focus is on the final descent phase when the pilot controls the aircraft manually based on the flight director commands. The proposed model is developed based on an existing model as well as highly experienced pilot's comments. A flight simulator experiment is conducted and three pilots’ landing data are obtained. The parameters of the pilot model are tuned via a genetic algorithm. The simulation result reveals that the proposed model captures well the characteristics of the data obtained in the simulator experiment and shows a good accordance with actual command tracking capability. The obtained parameters also identify the difference of control strategies between the pilots.

Emulation of pilot control behavior across a Stewart platform simulator

SUMMARYThis paper presents a model-based controller consisting of a feedback linearization scheme and a state-dependent proportional derivative (PD) controller adapted to a parallel flight simulator Stewart mechanism. This parallel robot is considered to emulate motions of highly maneuverable aircrafts, which require well-trained pilots. The simulations are based upon a reduced-model prototype built in order to verify kinematic design aspects and control laws. Indeterminacies in the mass distribution of the system will generally affect model-based controllers, necessitating compensation or the employment of robust control methods. Through introducing the pilot's sensorial feedback of acceleration, the pilot's behavior in giving commands is emulated via an optimization process, which tunes the controller coefficients accordingly. Stability of the designed control system is guaranteed via the Lyapunov approach. To further explore the system through perilous flight scenarios, three pre-designed maneuvers are selected as test cases. It is expected that closed-loop control tasks in which a pilot tracks a target, while at the same time the controller rejects disturbances and adapts itself to the pilot's progressive skills, are ameliorated through this arrangement. Numerical results show that the proposed method is found robust in the training process in conditions of parameters indeterminacy.

A Cybernetic Analysis of Maximum Unnoticeable Added Dynamics for Different Baseline Controlled Systems

Maximum unnoticeable added dynamics (MUAD) envelopes have been largely used to assess the adequacy of low-order equivalent systems (LOES) in handling qualities assessment and simulator validation. However, research has shown that more thorough verification of the adequacy of this method is required. This paper studies the influence of the baseline aircraft dynamics on the MUAD envelopes. The assessment is based on quantitative measures of pilot control behaviour obtained with the cybernetic approach. The measures were taken from a human-in-the-loop pitch tracking task experiment with compensatory display. The results are consistent with the MUAD envelopes and reveal no interaction effects of the baseline and added dynamics on the pilot control behaviour. This suggests that, under the considered conditions, the MUAD envelopes shall remain constant independently of the bandwidth of the baseline controlled dynamics.

Analysis of Pilot-Induced-Oscillation and Pilot Vehicle System Stability Using UAS Flight Experiments

This paper reports the results of a Pilot-Induced Oscillation (PIO) and human pilot control characterization study performed using flight data collected with a Remotely Controlled (R/C) unmanned research aircraft. The study was carried out on the longitudinal axis of the aircraft. Several existing Category 1 and Category 2 PIO criteria developed for manned aircraft are first surveyed and their effectiveness for predicting the PIO susceptibility for the R/C unmanned aircraft is evaluated using several flight experiments. It was found that the Bandwidth/Pitch rate overshoot and open loop onset point (OLOP) criteria prediction results matched flight test observations. However, other criteria failed to provide accurate prediction results. To further characterize the human pilot control behavior during these experiments, a quasi-linear pilot model is used. The parameters of the pilot model estimated using data obtained from flight tests are then used to obtain information about the stability of the Pilot Vehicle System (PVS) for Category 1 PIOs occurred during straight and level flights. The batch estimation technique used to estimate the parameters of the quasi-linear pilot model failed to completely capture the compatibility nature of the human pilot. The estimation results however provided valuable insights into the frequency characteristics of the human pilot commands. Additionally, stability analysis of the Category 2 PIOs for elevator actuator rate limiting is carried out using simulations and the results are compared with actual flight results.

Manual Control Adaptation to Changing Vehicle Dynamics in Roll–Pitch Control Tasks

This paper investigates how pilot control behavior adapts to time-varying vehicle dynamics in a roll–pitch control task. Nine general aviation pilots performed eight experimental conditions in which the axis containing the time-varying controlled dynamics and the rate of change of the dynamics varied. To characterize time-varying human control behavior, a maximum likelihood estimation procedure was used to estimate the parameters of a pilot model with time-dependent sigmoid functions. Pilot control behavior in both axes was significantly affected by the time-varying controlled dynamics in roll and pitch and by the rate of change of the dynamics. Control behavior was mainly affected in the axis containing the time-varying controlled dynamics. However, control behavior in the axis not containing the time-varying dynamics was also affected, indicating cross coupling in human perception and control processes between roll and pitch. The maximum likelihood estimation method provided accurate parameter estimations when applied to a pilot model with time-dependent sigmoid functions. The parameters defining pilots’ equalization dynamics after the transition in controlled dynamics and the maximum rate of change of the equalization dynamics had the lowest estimation accuracy.

Aircraft-Pilot System Modeling and Pilot Control Behavior Research for Airdrop Task

Abstract: Adverse aircraft-pilot coupling during the process of transport airdrop can lower the level of flight safety. Pilot's rational control behavior can avoid adverse aircraft-pilot coupling. In this paper, the model of aircraft-pilot system consisting of motion body model, task model and pilot model is built at first. Three different pilot control methods are investigated for airdrop. The first one is continuous pitch compensatory control, the second one is elevator maintenance control, and the third one is precognitive control based on the knowledge of flight tendency during airdrop. Two different precognitive control methods are designed. Models of those pilot control methods are constituted and numerical simulations are conducted. In addition, for exploration on feasibility of those methods, a series of pilot-in-loop real-time experiments are performed in a fixed flight simulator. Real-time experiments match well with numerical simulation results which validate different effects of those methods on airdrop. The aircraft performs most satisfactorily under the two precognitive control methods. The study is of considerable significance to investigate of which kind of pilot control method to be applied during airdrop.

A model for pilot control behavior in analyzing potential loss-of-control events

An adaptive model of the human pilot engaged in pursuit tracking tasks that was previously introduced in the literature is modified and applied to the analysis of piloted control of a realistic transport aircraft model. As described, the pilot model requires no guesswork on the part of the analyst as regards initial parameter settings. By means of computer simulation, the adaptive pilot model is shown to exhibit superior performance to its non-adaptive counterpart in a series of configuration changes associated with the vehicle model. The overall validity of the post-adaptive pilot model is assessed by examining the resulting open-loop pilot vehicle dynamics in comparison to that predicted by the crossover model of the human pilot. The pilot modeling approach is proposed as a preliminary analytical tool to be used in the assessment of robust flight control system designs subject to faults or system failures with an eye toward potential loss-of-control.

Framework for Flight Loads Analysis of Trajectory-Based Manoeuvres with Pilot Models

A framework is presented to allow the investigation of interactions between manual control and flight control systems for large flexible aircraft. It allows the fast simulation of particular flight test manoeuvres designed to expose unwanted interactions between the pilot and aircraft flight dynamics. It combines a trajectory generation scheme and an aeroelastic aircraft model together with pilot models to conduct flight loads analysis relevant to trajectory-based flight test manoeuvres. The ability of the framework to assess the impact of variations in pilot control characteristics on flight loads is illustrated through the simulation of two manoeuvres. The first required the pilot to align the aircraft from an offset position in minimum time and the second required avoiding an obstacle by following a four-dimensional trajectory. Pilot models representative of pilot control behavior were derived by applying a parameter identification scheme to data gathered through a series of manual control experiments. The pilot models were coupled with a nonlinear flexible aircraft model to demonstrate the effects on pilot–vehicle system frequency response due to changes in task and intersubject differences. Worst case wing loads were then obtained and compared to aircraft loads envelopes.

Pilot Control Behavior Analysis Using Cutoff Frequency and Power Frequency for a Civil Transport Aircraft Encountering Turbulence Based on Flight Simulation

Atmospheric turbulence is one of the leading causes of serious personal injuries in nonfatal accidents of commercial aircraft and poses a significant hazard to aircraft in the terminal area. The pilot control behavior, workload and its difference from the normal flight situation also have essential impact on flight safety when the airplane encountered turbulence. In this paper, a unique frequency domain method, which used the cutoff frequency and the power frequency as the key metrics, was utilized to analyze the pilot control behavior in turbulence environment for a civil transport aircraft based on piloted flight simulation data. The results show that the cutoff frequency and power frequency consider both the frequency of pilot activity and the level of the activity at the same time, and could be a useful tool to analyze the pilot control behavior.

Influences of Simulator Motion System Characteristics on Pilot Control Behavior

Low-cost motion systems have been proposed for certain training tasks that would otherwise be performed on high-performance full-flight simulators. These systems usually have lower bandwidth and lower smoothness. The influence of these characteristics on pilot perception and control behavior is unknown and needs to be investigated. In this paper, this is done by simulating a model of a simulator with limited capabilities on a high-end simulator. The platform limitations, which consist of a platform filter, time delay, and noise characteristics, can then be removed one by one, and their effect on control behavior is studied in isolation. An experiment was conducted to identify pilot perception and control behavior in a closed-loop control task. The time delay and noise characteristics of the simulators did not have an effect. However, it was found that the bandwidth of the motion system had a significant effect on performance and control behavior. Results indicate that the motion cues were barely used at all in conditions with a low bandwidth, and that participants relied on the visual cues to generate lead to perform the control task.

Cross-platform validation for a model of a low-cost Stewart platform

Low-cost motion systems have been proposed for certain training tasks that would otherwise be performed on high-performance full flight simulators. These systems have shorter stroke actuators, lower bandwidth, and higher motion noise. The influence of these characteristics on pilot perception and control behavior is unknown, and needs to be investigated. A possible approach to this would be to simulate a platform with limited capabilities with a high-end platform, and then remove the platform limitations one by one. The effects of these platform limitations on pilot behavior can then be investigated in isolation. In this paper, a model of a low-cost simulator was validated for simulation on a high-performance simulator. A dynamic model of the MPI Stewart platform was analyzed and compared with measurements of the baseline simulator response. Measurements for validation of the implementation of the model on the SIMONA Research Simulator showed that the dynamics of the MPI Stewart platform could be represented well in terms of dynamic range, time delay, and noise characteristics. The implementation of the model of the MPI Stewart platform will be used in experiments on the effects of these characteristics on pilot control behavior.

Modeling Wide-Frequency-Range Pilot Equalization for Control of Aircraft Pitch Dynamics

In continuous manual control tasks, human controllers adapt their control strategy to the dynamics of the controlled element. This compensation for the controlled-element dynamics is performed around the pilot–vehicle system crossover frequency, in order to obtain satisfactory performance of the combined pilot–vehicle system, but is also seen to extend to frequencies well above crossover. For a controlled element representing the linearized pitch dynamics of a small conventional jet aircraft, an extension to the models for pilot equalization described in the literature was found to be needed for the modeling of the adopted pilot equalization dynamics over a wide frequency range. Measured pilot describing functions revealed that pilots use a combination of low-frequency lag and high-frequency lead equalization to compensate for the characteristics of these typical aircraft pitch dynamics around the short-period mode. An additional high-frequency lead term in the pilot equalization transfer function was found to allow for the modeling of these adopted equalization dynamics over a wide frequency range, thereby also yielding a significant increase in the percentage of measured control inputs that is explained by the pilot model. Furthermore, for this controlled element the extended model for the equalization dynamics was found to be important for the interpretation of the changes in pilot control behavior that occur due to the presence of physical motion feedback.

A Criterion Based on Closed-loop Pilot-aircraft Systems for Predicting Flying Qualities

During the process of aircraft design, the mathematical model of pilot control behavior characteristics is always used to predict aircraft flying qualities (FQ). This is one of the important methods to avoid pilot-aircraft adverse coupling. In order to study the FQ criterion based on closed-loop pilot-aircraft systems, first, an experimental database is built, which includes 40 aircraft dynamics configurations and the corresponding flight simulation results. Second, the mathematical pilot models with a set of different aircraft configurations are obtained by this experimental database. Then, two FQ criteria, Neal-Smith criterion and Moscow Aviation Institute (MAI) criterion, are analyzed. And the relationship between the FQ level evaluated by actual pilot and the parameters of closed-loop pilot-aircraft systems is studied. Finally, an improved criterion of aircraft FQ is built based on the above two criteria. This new criterion is further used to predict FQ for four new aircraft dynamics configurations, and the prediction results verify its accuracy and practicability.

Identification of Multimodal Pilot Control Behavior in Real Flight

Flight simulators are widely used for research and training of pilots. However, in skill-based control tasks, pilots behave differently in the simulator compared to real flight, due to limited visual and physical motion cues. This warrants a method that quantifies simulator fidelity by the differences between pilot control behavior in real flight and in the simulator. This paper presents the results of in-flight experiments to determine multimodal pilot control behavior in real flight, the baseline in determining simulator fidelity. The experiment is performed in a Cessna Citation II laboratory aircraft with a custom-built fly-by-wire system. To estimate pilots' visual and vestibular responses, two forcing functions need to be inserted into the control loop at different locations. The fly-by-wire system was used to physically disturb the aircraft with a disturbance forcing function, while pilots had to track a target forcing function on a display in the cockpit. Both a multisine and a ramp target signal were tested in roll and pitch control tasks, resulting in four experimental conditions. The results show that multimodal pilot control behavior can indeed be identified in real flight using the current fly-by-wire system setup. For two pilots, pilot model parameters could be estimated with high accuracy for all conditions. For some conditions of the two remaining pilots, however, no accurate parameter estimates could be found, as their control activity did not allow for a stable global optimum of the parameter estimation problem.

Effects of Heave Washout Settings in Aircraft Pitch Disturbance Rejection

In most moving-base flight simulators, the simulated aircraft motion needs to be filtered with motion washout filters to keep the simulator within its limited motion envelope. Translational motion in particular requires filtering, as the low frequency components of the vehicle motion tend to quickly drive simulators toward their motion bounds. Commonly, linear washout filters are therefore used to attenuate the simulated motion in magnitude and in phase. It is found in many studies that the settings of these washout filters affect pilot performance and control behavior. In most of these studies, no comparison to a case with one-to-one motion cues is performed, as a result of the limited motion envelope of the used simulators. In the current study, an experiment was performed in the SIMONA Research Simulator at Delft University of Technology to investigate the effects of heave washout settings on pilot performance and control behavior in a pitch attitude control task. In addition to rotational pitch motion, heave accelerations at the pilot station that result directly from aircraft pitch were evaluated. This heave motion component could be supplied one-to-one in the simulator due to the modest size of the aircraft model, a Cessna Citation I business jet. The experiment revealed that pilot performance and control activity both increased significantly with increasing heave motion fidelity. An analysis of pilot control behavior using pilot models indicated that the enhanced performance was caused by an increase in the magnitude with which pilots responded to visual and physical motion stimuli and a decrease in the amount of visual lead that was generated by the pilots.

A Cybernetic Approach to Assess Flight Simulator Motion Fidelity

Due to a limited understanding of human multimodal motion perception during aircraft control, the definition of requirements for flight simulator motion fidelity is a problem the flight simulation community has struggled with for years. The development of adequate tuning procedures for motion washout algorithms has remained problematic for the same reason. This paper proposes a method for assessment of simulator motion fidelity that makes use of a cybernetic, model-based approach to measuring multimodal pilot control behavior. As illustrated here with data from a recent human-in-the-loop experiment, this approach allows for objective detection of changes in pilot control that result from degraded simulator motion fidelity.

Multimodal Pilot Control Behavior in Combined Target-Following Disturbance-Rejection Tasks

Investigating how humans use their perceptual modalities while controlling a vehicle is important for the design of new control systems and the optimization of simulator motion cueing. For the identification of separate pilot response functions to the different perceived cues, multiple forcing functions need to be inserted into the manual control loop. An example of a task with multiple forcing functions is a combined target-following disturbance-rejection task, where a target and disturbance signal are used to separate the human visual and vestibular motion responses. The use of multiple forcing functions, however, also affects the nature of the control task and how the motion cues are used by the pilot to form a proper control action. This paper presents the results of an experiment where possible effects of using multiple forcing functions on pilot control behavior in an aircraft pitch control task are investigated. The results indicate that pilot performance and control activity are significantly lower when the relative power of the target forcing function is increased. This is caused by a significant change in multimodal pilot control behavior. With an increase in relative target power, the visual-perception gain is reduced and the visual time delay becomes higher. The motion-perception gain reduces if both forcing functions have significant power. It is also found that multimodal pilot control behavior in a pure target or disturbance task can be analyzed by adding a small additional disturbance or target signal, respectively. In this case, the effects on control behavior are found to be minimal, while still being able to accurately estimate the parameters of the multichannel pilot model.