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I. Miletović
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8 records found
1
Journal article
(2021)
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I. Miletović, M.D. Pavel, D.M. Pool, O. Stroosma, M.M. van Paassen, Max Mulder, Mark Wentink
Eigenmode distortion is a novel quantitative methodology developed to objectively evaluate motion cueing fidelity in flight simulation. It relies on an explicit coupling of linearized vehicle and Motion Cueing Algorithm dynamics. Modal analysis subsequently performed on this coupled system reveals the degree of distortion imposed by the Motion Cueing Algorithm on to the dynamics of the simulated vehicle. Eigenmode distortion thereby provides unprecedented insight into the combined dynamics of the two systems along modal coordinates. Compared with existing methods for motion cueing fidelity assessment, the eigenmode distortion method enables a systematic analysis of the coupled vehicle and Motion Cueing Algorithm dynamics. This is mainly because it does not consider the Motion Cueing Algorithm in isolation and does not inherently rely on assumptions regarding the excitation of the simulated vehicle dynamics. This paper outlines the theoretical foundation of the eigenmode distortion method and includes a case study on helicopter longitudinal dynamics and a sensitivity analysis to demonstrate its utility. The results presented in this paper shown that the eigenmode distortion method can reveal interactions between the Motion Cueing Algorithm and the vehicle dynamics that are currently not captured by other established methods, such as the Sinacori–Schroeder criteria and the Objective Motion Cueing Test.
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Eigenmode distortion is a novel quantitative methodology developed to objectively evaluate motion cueing fidelity in flight simulation. It relies on an explicit coupling of linearized vehicle and Motion Cueing Algorithm dynamics. Modal analysis subsequently performed on this coupled system reveals the degree of distortion imposed by the Motion Cueing Algorithm on to the dynamics of the simulated vehicle. Eigenmode distortion thereby provides unprecedented insight into the combined dynamics of the two systems along modal coordinates. Compared with existing methods for motion cueing fidelity assessment, the eigenmode distortion method enables a systematic analysis of the coupled vehicle and Motion Cueing Algorithm dynamics. This is mainly because it does not consider the Motion Cueing Algorithm in isolation and does not inherently rely on assumptions regarding the excitation of the simulated vehicle dynamics. This paper outlines the theoretical foundation of the eigenmode distortion method and includes a case study on helicopter longitudinal dynamics and a sensitivity analysis to demonstrate its utility. The results presented in this paper shown that the eigenmode distortion method can reveal interactions between the Motion Cueing Algorithm and the vehicle dynamics that are currently not captured by other established methods, such as the Sinacori–Schroeder criteria and the Objective Motion Cueing Test.
The Perceptual Eigenmode Distortion (PEMD), an extension to the Eigenmode Distortion (EMD), is a method for objectively evaluating simulator motion fidelity, developed over the last few years. EMD assesses how the Motion Cueing Algorithm (MCA) distorts the vehicle's perceived eigenmodes. In this paper, EMD is extended by a human perception model, which helps to balance the various motion cue contributions in a more human-centered context. Additionally, a new automatic MCA tuning approach is introduced to create an MCA parameter set that is optimal in terms of eigenmode distortion. The method is applied to a combined linear model of the Cessna Citation 500 for asymmetrical flight and the Classical Washout Algorithm (CWA). A pilot-in-the-loop experiment was performed, with six pilots in the SIMONA Research Simulator, to compare the PEMD method's parameter set with sets designed with the current state-of-the-art method of the Objective Motion Cueing Test (OMCT), and with a baseline motion configuration, as well as a condition without any simulator motion. Throughout each run of the double-blind pairwise comparisons, the Dutch roll eigenmode was externally excited with a gust of semi-random amplitude and direction. Two hypotheses were tested using subjective preferences and through measuring the Dutch roll suppression performance. Subjective preferences varied between and within pilots, and similar results for PEMD and OMCT were found. A significant improvement in performance was found, however, between the no-motion condition and the PEMD. Although the perceived differences between a PEMD-tuned and alternative MCA settings seem very subtle, the improved mode suppression performance suggests the method having merit in flight scenarios where the aircraft's dynamic modes play an important role.
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The Perceptual Eigenmode Distortion (PEMD), an extension to the Eigenmode Distortion (EMD), is a method for objectively evaluating simulator motion fidelity, developed over the last few years. EMD assesses how the Motion Cueing Algorithm (MCA) distorts the vehicle's perceived eigenmodes. In this paper, EMD is extended by a human perception model, which helps to balance the various motion cue contributions in a more human-centered context. Additionally, a new automatic MCA tuning approach is introduced to create an MCA parameter set that is optimal in terms of eigenmode distortion. The method is applied to a combined linear model of the Cessna Citation 500 for asymmetrical flight and the Classical Washout Algorithm (CWA). A pilot-in-the-loop experiment was performed, with six pilots in the SIMONA Research Simulator, to compare the PEMD method's parameter set with sets designed with the current state-of-the-art method of the Objective Motion Cueing Test (OMCT), and with a baseline motion configuration, as well as a condition without any simulator motion. Throughout each run of the double-blind pairwise comparisons, the Dutch roll eigenmode was externally excited with a gust of semi-random amplitude and direction. Two hypotheses were tested using subjective preferences and through measuring the Dutch roll suppression performance. Subjective preferences varied between and within pilots, and similar results for PEMD and OMCT were found. A significant improvement in performance was found, however, between the no-motion condition and the PEMD. Although the perceived differences between a PEMD-tuned and alternative MCA settings seem very subtle, the improved mode suppression performance suggests the method having merit in flight scenarios where the aircraft's dynamic modes play an important role.
Motion Cueing Fidelity in Rotorcraft Flight Simulation
A New Perspective using Modal Analysis
Doctoral thesis
(2020)
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Ivan Miletović
Flight simulators, or Flight Simulation Training Devices (FSTDs), offer great benefits in terms of safety and cost associated with pilot training and certification. To warrant uniform certification standards and to prevent adverse pilot training, (sub)system fidelity requirements are imposed by the Federal Aviation Authority (FAA) and European Aviation Safety Agency (EASA). While comprehensive, a notable example of an area in which these requirements are somewhat limited, are those pertaining to the Motion Cueing System (MCS) of full-flight flight simulators. The MCS comprises hardware, typically a set of actuators to enable physical motion of the platform, and software, often termed the Motion Cueing Algorithm (MCA), to process the simulated vehicle motion to prevent violation of (physical) simulator constraints. Naturally, the MCA introduces a significant mismatch between the actual (i.e., in-flight) and simulated vehicle motion perceived by the pilot. Furthermore, this mismatch often comes on top of inaccuracies in the mathematical model used to compute the simulated vehicle motion. Because of this complex interaction, the formulation of quantitative requirements pertaining to the allowed mismatch between real vehicle and simulator motion has proven cumbersome. To date, certification of flight simulator motion is therefore based predominantly on subjective evaluation by experienced pilots. To address this problem, the aim of this dissertation is to develop a unifying tool to quantify motion cueing fidelity in helicopter flight simulation and to evaluate its suitability in realistic applications.
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Flight simulators, or Flight Simulation Training Devices (FSTDs), offer great benefits in terms of safety and cost associated with pilot training and certification. To warrant uniform certification standards and to prevent adverse pilot training, (sub)system fidelity requirements are imposed by the Federal Aviation Authority (FAA) and European Aviation Safety Agency (EASA). While comprehensive, a notable example of an area in which these requirements are somewhat limited, are those pertaining to the Motion Cueing System (MCS) of full-flight flight simulators. The MCS comprises hardware, typically a set of actuators to enable physical motion of the platform, and software, often termed the Motion Cueing Algorithm (MCA), to process the simulated vehicle motion to prevent violation of (physical) simulator constraints. Naturally, the MCA introduces a significant mismatch between the actual (i.e., in-flight) and simulated vehicle motion perceived by the pilot. Furthermore, this mismatch often comes on top of inaccuracies in the mathematical model used to compute the simulated vehicle motion. Because of this complex interaction, the formulation of quantitative requirements pertaining to the allowed mismatch between real vehicle and simulator motion has proven cumbersome. To date, certification of flight simulator motion is therefore based predominantly on subjective evaluation by experienced pilots. To address this problem, the aim of this dissertation is to develop a unifying tool to quantify motion cueing fidelity in helicopter flight simulation and to evaluate its suitability in realistic applications.
Conference paper
(2019)
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Stanimir Stoev, Rene van Paassen, Olaf Stroosma, Ivan Miletovic, Max Mulder
The Eigenmode Distortion (EMD) analysis is a novel method for objective evaluation of simulator motion cueing fidelity, developed at Delft University of Technology. It expresses the distortions of the perceived motion cues in terms of the dynamic modes of a linear model of the vehicle and has been applied to assess rotorcraft simulations. This paper presents the adaptation of EMD for fixed wing aircraft, including performing the analysis at the pilot station instead of the centre of gravity. The method is applied to a combined linear model of a Cessna Citation 500 aircraft and the Classical Washout Algorithm (CWA). EMD is compared to the current state-of-the-art objective method, the Objective Motion Cueing Test (OMCT), which does not consider the dynamics of the simulated vehicle in its analysis. The two methods show different results in their cueing fidelity assessment of fourCWA configurations. An experiment with six pilots is performed in the SIMONA Research Simulator to test the capability of EMD and OMCT to predict the cueing fidelity as perceived by pilots. The subjects perform pairwise comparisons between the four CWA configurations by exciting the short period dynamics of the aircraft. Results indicate that preferences vary considerably between pilots, causing both EMD and OMCT to show poor, but similar, predictive capabilities.
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The Eigenmode Distortion (EMD) analysis is a novel method for objective evaluation of simulator motion cueing fidelity, developed at Delft University of Technology. It expresses the distortions of the perceived motion cues in terms of the dynamic modes of a linear model of the vehicle and has been applied to assess rotorcraft simulations. This paper presents the adaptation of EMD for fixed wing aircraft, including performing the analysis at the pilot station instead of the centre of gravity. The method is applied to a combined linear model of a Cessna Citation 500 aircraft and the Classical Washout Algorithm (CWA). EMD is compared to the current state-of-the-art objective method, the Objective Motion Cueing Test (OMCT), which does not consider the dynamics of the simulated vehicle in its analysis. The two methods show different results in their cueing fidelity assessment of fourCWA configurations. An experiment with six pilots is performed in the SIMONA Research Simulator to test the capability of EMD and OMCT to predict the cueing fidelity as perceived by pilots. The subjects perform pairwise comparisons between the four CWA configurations by exciting the short period dynamics of the aircraft. Results indicate that preferences vary considerably between pilots, causing both EMD and OMCT to show poor, but similar, predictive capabilities.
Conference paper
(2018)
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Ivan MiletoviC, Marilena Pavel, Olaf Stroosma, Daan Pool, Rene van Paassen, Mark Wentink, Max Mulder
Eigenmode distortion (EMD) is a novel methodology developed to study the degradation of perceived vehicle dynamics as a result of motion cueing algorithms (MCA’s) applied in rotorcraft 2ight simulators. This paper brie2y introduces EMD and subsequently describes its application in a pilot-in-the-loop experiment conducted on the SIMONA Research Simulator at Delft University of Technology. The experiment considers a precision hover task performed by two test pilots in three different motion cueing conditions. Each of the evaluated conditions is devised such to best reproduce one of the vehicle modes (pitch/heave subsidences and phugoid) simulated using an independently developed, three degree-of-freedom, longitudinal, nonlinear model of the AH-†„ Apache helicopter. The experiment yielded a number of interesting results. For example, the mode participation factors (MPFs) computed using recorded model states showed that the unstable phugoid mode dominates the overall dynamic response in all conditions evaluated. Also, based on the relative distribution of MPF’s across the three motion conditions, some indication of a change in pilot control behaviour as a result of motion cues (or lack thereof) was exposed. Finally, subjective pilot ratings suggest that the motion cueing condition optimized for the pitch subsidence mode is preferred, even though this is not the dominant mode in the vehicle’s response. The condition corresponding to the heave subsidence mode (i.e., only vertical motion cues) is appreciated least.
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Eigenmode distortion (EMD) is a novel methodology developed to study the degradation of perceived vehicle dynamics as a result of motion cueing algorithms (MCA’s) applied in rotorcraft 2ight simulators. This paper brie2y introduces EMD and subsequently describes its application in a pilot-in-the-loop experiment conducted on the SIMONA Research Simulator at Delft University of Technology. The experiment considers a precision hover task performed by two test pilots in three different motion cueing conditions. Each of the evaluated conditions is devised such to best reproduce one of the vehicle modes (pitch/heave subsidences and phugoid) simulated using an independently developed, three degree-of-freedom, longitudinal, nonlinear model of the AH-†„ Apache helicopter. The experiment yielded a number of interesting results. For example, the mode participation factors (MPFs) computed using recorded model states showed that the unstable phugoid mode dominates the overall dynamic response in all conditions evaluated. Also, based on the relative distribution of MPF’s across the three motion conditions, some indication of a change in pilot control behaviour as a result of motion cues (or lack thereof) was exposed. Finally, subjective pilot ratings suggest that the motion cueing condition optimized for the pitch subsidence mode is preferred, even though this is not the dominant mode in the vehicle’s response. The condition corresponding to the heave subsidence mode (i.e., only vertical motion cues) is appreciated least.
Accurate and reliable estimation of the kinematic state of a six degrees-of-freedom Stewart platform is a problem of interest in various engineering disciplines. Particularly so in the area of flight simulation, where the Stewart platform is in widespread use for the generation of motion similar to that experienced in actual flight. Accurate measurements of Stewart platform kinematic states are crucial for the application of advanced motion control algorithms and are highly valued in quantitative assessments of simulator motion fidelity. In the current work, a novel method for the reconstruction of the kinematic state of a Stewart platform is proposed. This method relies on an Unscented Kalman Filter (UKF) for a tight coupling of on-platform inertial sensors with measurements of the six actuator positions. The proposed algorithm is shown to be superior to conventional iterative methods in two main areas. First, more accurate estimates of motion platform velocity are obtained and, second, the algorithm is robust to inherent measurement uncertainties like noise and bias. The results were validated on the SIMONA Research Simulator (SRS) at TU Delft. To this end, an efficient implementation of the algorithm was driven, in real time, by actual sensor measurements from two representative motion profiles.
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Accurate and reliable estimation of the kinematic state of a six degrees-of-freedom Stewart platform is a problem of interest in various engineering disciplines. Particularly so in the area of flight simulation, where the Stewart platform is in widespread use for the generation of motion similar to that experienced in actual flight. Accurate measurements of Stewart platform kinematic states are crucial for the application of advanced motion control algorithms and are highly valued in quantitative assessments of simulator motion fidelity. In the current work, a novel method for the reconstruction of the kinematic state of a Stewart platform is proposed. This method relies on an Unscented Kalman Filter (UKF) for a tight coupling of on-platform inertial sensors with measurements of the six actuator positions. The proposed algorithm is shown to be superior to conventional iterative methods in two main areas. First, more accurate estimates of motion platform velocity are obtained and, second, the algorithm is robust to inherent measurement uncertainties like noise and bias. The results were validated on the SIMONA Research Simulator (SRS) at TU Delft. To this end, an efficient implementation of the algorithm was driven, in real time, by actual sensor measurements from two representative motion profiles.
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The fidelity of a rotorcraft flight simulator is influenced by many factors, such as the vehicle dynamic model and the motion cueing algorithm (MCA). To quantify the fidelity of a simulator objectively requires detailed knowledge of human pilot perception and control behaviour that is not yet available. As a consequence, subjective assessments made by qualified pilots remain the most important way to assess flight simulation fidelity. The use of standardized rating scales during such assessments can increase the level of objectivity above that provided by less structured evaluations. The current paper describes the result of an experiment performed on the Desdemona simulator to evaluate two rating scales, namely the Simulator Fidelity Rating (SFR) scale and the Motion Fidelity Rating (MFR) scale, as suitable indicators of flight simulation fidelity. In this experiment, two characteristics of the simulated environment were varied, namely rotorcraft dynamics and MCA configuration, and the type of rating scale used was treated as an additional independent variable. The primary results of the experiments suggest that pilots are able to recognize a strong decline in flight simulation fidelity when both rotorcraft dynamics and motion are degraded simultaneously. However, when either one of these characteristics are varied independently of the other, the results are inconclusive. The paper presents a more detailed review of the various results gathered during the experiment and formulates recommendations for future experiments in rotorcraft flight simulation fidelity assessment that involve the use of pilot ratings.
...
The fidelity of a rotorcraft flight simulator is influenced by many factors, such as the vehicle dynamic model and the motion cueing algorithm (MCA). To quantify the fidelity of a simulator objectively requires detailed knowledge of human pilot perception and control behaviour that is not yet available. As a consequence, subjective assessments made by qualified pilots remain the most important way to assess flight simulation fidelity. The use of standardized rating scales during such assessments can increase the level of objectivity above that provided by less structured evaluations. The current paper describes the result of an experiment performed on the Desdemona simulator to evaluate two rating scales, namely the Simulator Fidelity Rating (SFR) scale and the Motion Fidelity Rating (MFR) scale, as suitable indicators of flight simulation fidelity. In this experiment, two characteristics of the simulated environment were varied, namely rotorcraft dynamics and MCA configuration, and the type of rating scale used was treated as an additional independent variable. The primary results of the experiments suggest that pilots are able to recognize a strong decline in flight simulation fidelity when both rotorcraft dynamics and motion are degraded simultaneously. However, when either one of these characteristics are varied independently of the other, the results are inconclusive. The paper presents a more detailed review of the various results gathered during the experiment and formulates recommendations for future experiments in rotorcraft flight simulation fidelity assessment that involve the use of pilot ratings.