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At least 307 records · Page 17

Developing a Fundamental Model for an Integrated GPS/INS State Estimation System with Kalman Filtering

This work will demonstrate the integration of sensor and system dynamic data and their appropriate models using an optimal filter to create a robust, adaptable, easily reconfigurable state (motion) estimation system. This state estimation system will clearly show the application of fundamental modeling and filtering techniques. These techniques are presented at a general, first principles level, that can easily be adapted to specific applications. An example of such an application is demonstrated through the development of an integrated GPS/INS navigation system. This system acquires both global position data and inertial body data, to provide optimal estimates of current position and attitude states. The optimal states are estimated using a Kalman filter. The state estimation system will include appropriate error models for the measurement hardware. The results of this work will lead to the development of a "black-box" state estimation system that supplies current motion information (position and attitude states) that can be used to carry out guidance and control strategies. This black-box state estimation system is developed independent of the vehicle dynamics and therefore is directly applicable to a variety of vehicles. Issues in system modeling and application of Kalman filtering techniques are investigated and presented. These issues include linearized models of equations of state, models of the measurement sensors, and appropriate application and parameter setting (tuning) of the Kalman filter. The general model and subsequent algorithm is developed in Matlab for numerical testing. The results of this system are demonstrated through application to data from the X-33 Michael's 9A8 mission and are presented in plots and simple animations.

Canfield, Stephen↗

Application of an Ensemble Smoother to Precipitation Assimilation

Assimilation of precipitation in a global modeling system poses a special challenge in that the observation operators for precipitation processes are highly nonlinear. In the variational approach, substantial development work and model simplifications are required to include precipitation-related physical processes in the tangent linear model and its adjoint. An ensemble based data assimilation algorithm "Maximum Likelihood Ensemble Smoother (MLES)" has been developed to explore the ensemble representation of the precipitation observation operator with nonlinear convection and large-scale moist physics. An ensemble assimilation system based on the NASA GEOS-5 GCM has been constructed to assimilate satellite precipitation data within the MLES framework. The configuration of the smoother takes the time dimension into account for the relationship between state variables and observable rainfall. The full nonlinear forward model ensembles are used to represent components involving the observation operator and its transpose. Several assimilation experiments using satellite precipitation observations have been carried out to investigate the effectiveness of the ensemble representation of the nonlinear observation operator and the data impact of assimilating rain retrievals from the TMI and SSM/I sensors. Preliminary results show that this ensemble assimilation approach is capable of extracting information from nonlinear observations to improve the analysis and forecast if ensemble size is adequate, and a suitable localization scheme is applied. In addition to a dynamically consistent precipitation analysis, the assimilation system produces a statistical estimate of the analysis uncertainty.

Zhang, Sara↗

An Integrated Approach to Damage Accommodation in Flight Control

In this paper we present an integrated approach to in-flight damage accommodation in flight control. The approach is based on Multiple Models, Switching and Tuning (MMST), and consists of three steps: In the first step the main objective is to acquire a realistic aircraft damage model. Modeling of in-flight damage is a highly complex problem since there is a large number of issues that need to be addressed. One of the most important one is that there is strong coupling between structural dynamics, aerodynamics, and flight control. These effects cannot be studied separately due to this coupling. Once a realistic damage model is available, in the second step a large number of models corresponding to different damage cases are generated. One possibility is to generate many linear models and interpolate between them to cover a large portion of the flight envelope. Once these models have been generated, we will implement a recently developed-Model Set Reduction (MSR) technique. The technique is based on parameterizing damage in terms of uncertain parameters, and uses concepts from robust control theory to arrive at a small number of "centered" models such that the controllers corresponding to these models assure desired stability and robustness properties over a subset in the parametric space. By devising a suitable model placement strategy, the entire parametric set is covered with a relatively small number of models and controllers. The third step consists of designing a Multiple Models, Switching and Tuning (MMST) strategy for estimating the current operating regime (damage case) of the aircraft, and switching to the corresponding controller to achieve effective damage accommodation and the desired performance. In the paper present a comprehensive approach to damage accommodation using Model Set Design,MMST, and Variable Structure compensation for coupling nonlinearities. The approach was evaluated on a model of F/A-18 aircraft dynamics under control effector damage, augmented by nonlinear cross-coupling terms and a structural dynamics model. The proposed approach achieved excellent performance under severe damage effects.

Boskovic, Jovan D.↗

Flight Dynamics Aspects of a Large Civil Tiltrotor Simulation Using Translational Rate Command

An in-depth analysis of a Large Civil Tiltrotor simulation with a Translational Rate Command control law that uses automatic nacelle deflections for longitudinal velocity control and lateral cyclic for lateral velocity control is presented. Results from piloted real-time simulation experiments and offline time and frequency domain analyses are used to investigate the fundamental flight dynamic and control mechanisms of the control law. The baseline Translational Rate Command conferred handling qualities improvements over an attitude command attitude hold control law but in some scenarios there was a tendency to enter PIO. Nacelle actuator rate limiting strongly influenced the PIO tendency and reducing the rate limits degraded the handling qualities further. Counterintuitively, increasing rate limits also led to a worsening of the handling qualities ratings. This led to the identification of a nacelle rate to rotor longitudinal flapping coupling effect that induced undesired pitching motions proportional to the allowable amount of nacelle rate. A modification that applied a counteracting amount of longitudinal cyclic proportional to the nacelle rate significantly improved the handling qualities. The lateral axis of the Translational Rate Command conferred Level 1 handling qualities in a Lateral Reposition maneuver. Analysis of the influence of the modeling fidelity on the lateral flapping angles is presented. It is showed that the linear modeling approximation is likely to have under-predicted the side-force and therefore under-predicted the lateral flapping at velocities above 15 ft/s. However, at lower velocities, and therefore more weakly influenced by the side force modeling, the accelerations that the control law commands also significantly influenced the peak levels of lateral flapping achieved.

Lawrence, Ben↗

Machine Learning for the Prediction of Local Asteroid Damages

Risk assessment studies of local asteroid hazards traditionally simulate the physics of meteors with engineering models tailored to analyze tens-of-millions of scenarios. However, these simplified approaches still need to solve time-dependent ODEs to model the entry process and the resulting ground damage. With a computational cost of O(0.01 CPU.s) per scenario, simulating these large numbers of potential entry conditions in risk assessment studies can take several days on local computers. To improve computational efficiency, we propose in this paper an orthogonal approach based on machine learning models to predict the size of damaged areas given a list of entry parameters. We train 5 machine learning methods and compare the predictions to the outputs of the PAIR model, first only with primitive entry condition variables, and then with more advanced features. We find that complex models like neural networks are well-suited to estimate blast hazards, while simpler linear models can accurately assess thermal damage. For both types of hazards, the radii of damaged areas can be predicted with around 10% average errors and a coefficient of determination (R2) of 0.99. The CPU time is decreased by a factor O(10 3 ) compared to the PAIR model, which enables the simulation of millions of scenarios in minutes, on a local computer. We then use the same machine learning approaches for a classification task where the models are trained to predict if an asteroid will produce a given level of damage. Results show that complex models like the gradient boosting classifier and the neural network can perform this task with 98% accuracy. Beyond surrogate models, we finally incorporate the machine learning algorithms to the state-of-the-art Shapley sensitivity analysis and present a ranking of the entry parameters based on their contributions to ground damages.

SMD↗

Helicopter derivative identification from analytic models and flight test data

Recent results of stability derivative identification from helicopter analytic models and flight test data are presented. Six and nine degree-of-freedom (DOF) linear models are identified from an analytic nonlinear helicopter simulation using a least square technique. The identified models are compared with the convectional partial differentiation method for obtaining derivatives to form the basis for interpretation of derivatives identified from flight data. Six degree-of-freedom models are identified from CH-53A and CH-54B flight data, using an extended Kalman filter modified to process several maneuvers simultaneously. The a priori derivative estimate is obtained by optimal filtering of the data and then using a least square method. The results demonstrate that a six DOF identified model is sufficient to determine the low frequency modes of motion, but a nine DOF rotor/body model is necessary for proper representation of short-term response.

Molusis, J. H.↗

Reynolds stress models of homogeneous turbulence

Existing and new models for the rapid and the return terms in the Reynolds stress equations were tested in two ways. One, by direct comparison of the model with simulation data. The other, by simulating the flows using the models and comparing the predicted Reynolds stresses with the data. It was found that existing linear models can be improved and that nonlinear models are in better agreement with the simulation data for a wide variety of flows.

Shih, T.-H.↗

Critical assessment of Reynolds stress turbulence models using homogeneous flows

In modeling the rapid part of the pressure correlation term in the Reynolds stress transport equations, extensive use has been made of its exact properties which were first suggested by Rotta. These, for example, have been employed in obtaining the widely used Launder, Reece and Rodi (LRR) model. Some recent proposals have dropped one of these properties to obtain new models. We demonstrate, by computing some simple homogeneous flows, that doing so does not lead to any significant improvements over the LRR model and it is not the right direction in improving the performance of existing models. The reason for this, in our opinion, is that violation of one of the exact properties can not bring in any new physics into the model. We compute thirteen homogeneous flows using LRR (with a recalibrated rapid term constant), IP and SSG models. The flows computed include the flow through axisymmetric contraction; axisymmetric expansion; distortion by plane strain; and homogeneous shear flows with and without rotation. Results show that for most general representation for a model linear in the anisotropic tensor, performs either better or as good as the other two models of the same level.

Shabbir, Aamir↗

An analytic modeling and system identification study of rotor/fuselage dynamics at hover

A combination of analytic modeling and system identification methods have been used to develop an improved dynamic model describing the response of articulated rotor helicopters to control inputs. A high-order linearized model of coupled rotor/body dynamics including flap and lag degrees of freedom and inflow dynamics with literal coefficients is compared to flight test data from single rotor helicopters in the near hover trim condition. The identification problem was formulated using the maximum likelihood function in the time domain. The dynamic model with literal coefficients was used to generate the model states, and the model was parametrized in terms of physical constants of the aircraft rather than the stability derivatives resulting in a significant reduction in the number of quantities to be identified. The likelihood function was optimized using the genetic algorithm approach. This method proved highly effective in producing an estimated model from flight test data which included coupled fuselage/rotor dynamics. Using this approach it has been shown that blade flexibility is a significant contributing factor to the discrepancies between theory and experiment shown in previous studies. Addition of flexible modes, properly incorporating the constraint due to the lag dampers, results in excellent agreement between flight test and theory, especially in the high frequency range.

Hong, Steven W.↗

An analytic modeling and system identification study of rotor/fuselage dynamics at hover

A combination of analytic modeling and system identification methods have been used to develop an improved dynamic model describing the response of articulated rotor helicopters to control inputs. A high-order linearized model of coupled rotor/body dynamics including flap and lag degrees of freedom and inflow dynamics with literal coefficients is compared to flight test data from single rotor helicopters in the near hover trim condition. The identification problem was formulated using the maximum likelihood function in the time domain. The dynamic model with literal coefficients was used to generate the model states, and the model was parametrized in terms of physical constants of the aircraft rather than the stability derivatives, resulting in a significant reduction in the number of quantities to be identified. The likelihood function was optimized using the genetic algorithm approach. This method proved highly effective in producing an estimated model from flight test data which included coupled fuselage/rotor dynamics. Using this approach it has been shown that blade flexibility is a significant contributing factor to the discrepancies between theory and experiment shown in previous studies. Addition of flexible modes, properly incorporating the constraint due to the lag dampers, results in excellent agreement between flight test and theory, especially in the high frequency range.

Hong, Steven W.↗

Measuring rapid ocean tidal earth orientation variations with very long baseline interferometry

Ocean tidal effects on universal time and polar motion (UTPM) are investigated at four nearly diurnal (K(sub 1), P(sub 1), O(sub 1), and Q(sub 1)) and four nearly semidiurnal (K(sub 2), S(sub 2), M(sub 2), and N(sub 2)) frequencies by analyzing very long baseline interferometry (VLBI) data extending from 1978 to 1992. We discuss limitations of comparisons between experiment and theory for the retograde nearly diurnal polar motion components due to their degeneracy with prograde components of the nutation model. Estimating amplitudes of contributions to the modeled VLBI observables at these eight frequencies produces a statistically highly significant improvement of 7 mm to the residuals of a fit to the observed delays. Use of such an improved UTPM model also reduces the 14-30 mm scatter of baseline lengths about a time-linear model of tectonic motion by 3-14 mm, also withhigh significance levels. A total of 28 UTPM ocean tidal amplitudes can be unambiguously estimated from the data, with resulting UTI and PM magnitudes as large as 21 micro secs and 270 microarc seconds and formal uncertainties of the order of 0.3 micro secs and 5 microarc secs for UTI and PM, respectively. Empirically determined UTPM amplitudes and phases are com1pared to values calculated theoretically by Gross from Seiler's global ocean tide model. The discrepancy between theory and experiment is larger by a factor of 3 for UTI amplitudes (9 micro secs) than for prograde PM amplitudes (42 microarc secs). The 14-year VLBI data span strongly attenuates the influence of mismodeled effects on estimated UTPM amplitudes and phases that are not coherent with the eight frequencies of interest. Magnitudes of coherent and quasi-coherent systematic errors are quantified by means of internal consistency tests. We conclude that coherent systematic effects are many times larger than the formal uncertainties and can be as large as 4 micro secs for UTI and 60 microarc secs for polar motion. On the basis of such ealistic error estimates, 22 of the 31 fitted UTPM ocean tidal amplitudes differ from zero by more than 2 sigma.

Sovers, O. J.↗

MIMO Sliding Mode Control for a Tailless Fighter Aircraft, An Alternative to Reconfigurable Architectures

A frequency-domain procedure for the design of sliding mode controllers for multi-input, multi-output (MIMO) systems is presented. The methodology accommodates the effects of parasitic dynamics such as those introduced by unmodeled actuators through the introduction of multiple asymptotic observers and model reference hedging. The design procedure includes a frequency domain approach to specify the sliding manifold, the observer eigenvalues, and the hedge model. The procedure is applied to the development of a flight control system for a linear model of the Innovative Control Effector (ICE) fighter aircraft. The stability and performance robustness of the resulting design is demonstrated through the introduction of significant degradation in the control effector actuators and variation in vehicle dynamics.

Wells, S. R.↗

Model-Based Control of an Aircraft Engine using an Optimal Tuner Approach

This paper covers the development of a model-based engine control (MBEC) method- ology applied to an aircraft turbofan engine. Here, a linear model extracted from the Commercial Modular Aero-Propulsion System Simulation 40,000 (CMAPSS40k) at a cruise operating point serves as the engine and the on-board model. The on-board model is up- dated using an optimal tuner Kalman Filter (OTKF) estimation routine, which enables the on-board model to self-tune to account for engine performance variations. The focus here is on developing a methodology for MBEC with direct control of estimated parameters of interest such as thrust and stall margins. MBEC provides the ability for a tighter control bound of thrust over the entire life cycle of the engine that is not achievable using traditional control feedback, which uses engine pressure ratio or fan speed. CMAPSS40k is capable of modeling realistic engine performance, allowing for a verification of the MBEC tighter thrust control. In addition, investigations of using the MBEC to provide a surge limit for the controller limit logic are presented that could provide benefits over a simple acceleration schedule that is currently used in engine control architectures.

Connolly, Joseph W.↗

Progress Towards Integrating the Finite-Volume Cubed-Sphere (FV3) Dynamical Core Tangent Linear and Adjoint Models into JEDI

The Joint Effort for Data assimilation Integration (JEDI) -- led by the Joint Center for Satellite Data Assimilation (JCSDA) -- is an inter-organizational endeavor to develop a common framework for performing data assimilation. This extensive framework will ultimately provide solvers, observation operators, interpolation and model interfaces using object oriented modeling. Two partners involved in JEDI use or plan to use the Finite Volume Cubed-Sphere (FV3) dynamical core to produce weather forecasts; these are NASA's Global Modeling and Assimilation Office and NOAA's National Center for Environment Prediction. In this work we present an update on ongoing efforts to integrate the FV3 tangent linear and adjoint models into the prototype JEDI framework. We setup and run a simple cycled data assimilation experiment using 4DVAR on the cubed sphere grid and with the FV3 tangent linear and adjoint models. Development of the observation operators for JEDI is separately underway. Instead of using real observations a simplified set of simulated observations will be used. We discuss the steps required to bring the FV3 linearized model into the object oriented framework and consider what would be the computational requirements of running this configuration for an operational system. FV3 uses a small time-step to ensure that small scales are well resolved, however this presents design challenges when running 4DVAR with the adjoint. An approach to storing the FV3 model trajectory has been developed that maintains the flexibility of using automatic differentiation. We discuss how this approach is incorporated into the framework. Other important uses of adjoint models include computing observation impacts and singular vectors, we consider how these tools can be included in JEDI.

Holdaway, Daniel↗

Aircraft control surface failure detection and isolation using the OSGLR test

The performance of the orthogonal series generalized likelihood ratio (OSGLR) test in detecting and isolating commercial aircraft control surface and actuator failures is evaluated. A modification to incorporate age-weighting which significantly reduces the sensitivity of the algorithm to modeling errors is presented. The steady-state implementation of the algorithm based on a single linear model valid for a cruise flight condition is tested using a nonlinear aircraft simulation. A number of off-nominal no-failure flight conditions including maneuvers, nonzero flap deflections, different turbulence levels and steady winds were tested. Based on the no-failure decision functions produced by off-nominal flight conditions, the failure detection and isolation performance at the nominal flight condition was determined. The extension of the algorithm to a wider flight envelope by scheduling on dynamic pressure and flap deflection is examined. Based on this testing, the OSGLR algorithm should be capable of detecting control surface failures that would affect the safe operation of a commercial aircraft. Isolation may be difficult if there are several surfaces which produce similar effects on the aircraft. Extending the algorithm over the entire operating envelope of a commercial aircraft appears feasible.

Bonnice, W. F.↗

Loop Shaping Control Design for a Supersonic Propulsion System Model Using Quantitative Feedback Theory (QFT) Specifications and Bounds

This paper covers the propulsion system component modeling and controls development of an integrated mixed compression inlet and turbojet engine that will be used for an overall vehicle Aero-Propulso-Servo-Elastic (APSE) model. Using previously created nonlinear component-level propulsion system models, a linear integrated propulsion system model and loop shaping control design have been developed. The design includes both inlet normal shock position control and jet engine rotor speed control for a potential supersonic commercial transport. A preliminary investigation of the impacts of the aero-elastic effects on the incoming flow field to the propulsion system are discussed, however, the focus here is on developing a methodology for the propulsion controls design that prevents unstart in the inlet and minimizes the thrust oscillation experienced by the vehicle. Quantitative Feedback Theory (QFT) specifications and bounds, and aspects of classical loop shaping are used in the control design process. Model uncertainty is incorporated in the design to address possible error in the system identification mapping of the nonlinear component models into the integrated linear model.

Connolly, Joseph W.↗

Multi-variable control of the GE T700 engine using the LQG/LTR design methodology

The design of scalar and multi-variable feedback control systems for the GET700 turboshaft engine coupled to a helicopter rotor system is examined. A series of linearized models are presented and analyzed. Robustness and performance specifications are posed in the frequency domain. The linear-quadratic-Gaussian with loop-transfer-recovery (LQG/LTR) methodology is used to obtain a sequence of three feedback designs. Even in the single-input/single-output case, comparison of the current control system with that derived from the LQG/LTR approach shows significant performance improvement. The multi-variable designs, evaluated using linear and nonlinear simulations, show even more potential for performance improvement.

Pfeil, W. H.↗

Multi-variable control of the GE T700 engine using the LQG/LTR design methodology

The design of scalar and multi-variable feedback control systems for the GE T700 turboshaft engine coupled to a helicopter rotor system is examined. A series of linearized models are presented and analyzed. Robustness and performance specifications are posed in the frequency domain. The linear-quadratic-Gaussian with loop-transfer-recovery (LQG/LTR) methodology is used to obtain a sequence of three feedback designs. Even in the single-input/single-output case, comparison of the current control system with that derived from the LQG/LTR approach shows significant performance improvement. The multi-variable designs, evaluated using linear and nonlinear simulations, show even more potential for performance improvement.

Pfeil, W. H.↗