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Rigidly forced oscillatory dynamic stability method for measuring pitch and yaw damping derivatives in wind tunnels at transonic and supersonic speeds
Insensitive flight control system design criteria was defined in terms of maximizing performance (handling qualities, RMS gust response, transient response, stability margins) over a defined parameter range. Wing load alleviation for the C-5A was chosen as a design problem. The C-5A model was a 79-state, two-control structure with uncertainties assumed to exist in dynamic pressure, structural damping and frequency, and the stability derivative, M sub w. Five new techniques (mismatch estimation, uncertainty weighting, finite dimensional inverse, maximum difficulty, dual Lyapunov) were developed. Six existing techniques (additive noise, minimax, multiplant, sensitivity vector augmentation, state dependent noise, residualization) and the mismatch estimation and uncertainty weighting techniques were synthesized and evaluated on the design example. Evaluation and comparison of these six techniques indicated that the minimax and the uncertainty weighting techniques were superior to the other six, and of these two, uncertainty weighting has lower computational requirements. Techniques based on the three remaining new concepts appear promising and are recommended for further research.
Comparative evaluation of seven insensitive synthesis techniques applied to the control of the longitudinal axis and symmetric flexure modes of the C-5A aircraft is described. These techniques have the common goal of achieving insensitivity to parameter uncertainties and unmodeled dynamics. For this comparison, the 'complete' model was assumed to consist of rigid body dynamics, fifteen flexure modes, unsteady aerodynamics, gust dynamics, and first order actuators for two control inputs. Thirteen flexure modes and the unsteady aerodynamics were treated as neglected dynamics. Dynamic pressure, structural frequency and damping, and the stability derivative were treated as uncertain parameters. Design specifications consisted of a transient response criterion, statistical response criteria, eigenvalue criteria and stability margins. A nominal controller designed without regard to sensitivity served as a benchmark for performance comparisons of the insensitive controllers.
A wind-tunnel investigation has been made at low speed to determine the effects of vertical fins placed ahead of the vertical tail on the directional stability and damping-in-yaw characteristics of a swept-wing model under steady-state oscillatory conditions. Various sizes of fins were used above and below the fuselage center line. The vertical-tail size also was varied.
Contains results of calculations made to determine the neutral oscillatory stability boundaries, period and time to damp of the oscillatory mode, and motions following disturbances. The calculations were made for Mach numbers of 0.75 and 2.3 at an attitude of 35,000 feet and for the landing condition at sea level.
The Neural Flight Control System (NFCS) was developed to address the need for control systems that can be produced and tested at lower cost, easily adapted to prototype vehicles and for flight systems that can accommodate damaged control surfaces or changes to aircraft stability and control characteristics resulting from failures or accidents. NFCS utilizes on a neural network-based flight control algorithm which automatically compensates for a broad spectrum of unanticipated damage or failures of an aircraft in flight. Pilot stick and rudder pedal inputs are fed into a reference model which produces pitch, roll and yaw rate commands. The reference model frequencies and gains can be set to provide handling quality characteristics suitable for the aircraft of interest. The rate commands are used in conjunction with estimates of the aircraft s stability and control (S&C) derivatives by a simplified Dynamic Inverse controller to produce virtual elevator, aileron and rudder commands. These virtual surface deflection commands are optimally distributed across the aircraft s available control surfaces using linear programming theory. Sensor data is compared with the reference model rate commands to produce an error signal. A Proportional/Integral (PI) error controller "winds up" on the error signal and adds an augmented command to the reference model output with the effect of zeroing the error signal. In order to provide more consistent handling qualities for the pilot, neural networks learn the behavior of the error controller and add in the augmented command before the integrator winds up. In the case of damage sufficient to affect the handling qualities of the aircraft, an Adaptive Critic is utilized to reduce the reference model frequencies and gains to stay within a flyable envelope of the aircraft.
Abstract Electric distribution networks increasingly host distributed energy resources based on power electronic converter (PEC) toward active distribution networks (ADN). Despite advances in computational capabilities, electromagnetic transient models are limited in scalability because of their reliance on exact data about the distribution system and each of its components. Similarly, the use of the DER_A model, which is intended to examine the combined dynamic behavior of many DERs, is limited by the difficulty in parameterization. There is a need for improved dynamic models of DERs for use in large power system simulations for stability analysis. This paper proposes an aggregate model‐free, data‐driven approach for deriving a dynamic partitioned model (DPM) of ADNs. Detailed residential distribution feeders were first developed, including PEC‐based DERs and composite load models (CMLDs), from which the aggregated DPM was derived. The performance was evaluated through various case studies and validated against the detailed ADN model and state‐of‐the‐art DER_A model with CMLD. The data‐driven DPM achieved a of over 90%, accurately representing the aggregated dynamic behavior of ADNs. Furthermore, the DPM significantly accelerated the simulation process with a computational speedup of 68 times compared to the detailed ADN and a 3.5 times speedup compared to the DER_A CMLD model.
Results from the First AIAA Stability and Control Prediction Workshop are summarized in this paper. The workshop series was developed in support of three primary objectives: (1) to establish best practices for the prediction of stability and control derivatives using industry-standard Computational Fluid Dynamics (CFD) solvers, (2) to provide an impartial forum for evaluating the effectiveness of Reynolds-averaged-Navier-Stokes- and Detached-Eddy-Simulation-based modeling techniques, and (3) to identify areas in need of additional research and development. To address these objectives, the inaugural workshop focused on generating computational aerodynamic predictions for the ONERA version of the NASA/Boeing Common Research Model. The configuration includes the wing, body, horizontal tail, and a vertical tail designed by ONERA. While longitudinal wind tunnel test data for the model had been previously documented, unpublished lateral test data at small sideslip angles provided a unique opportunity for participants to generate blind computational predictions for wind tunnel data comparisons. Additional test cases included assessments of the Mach number effect on static lateral/directional stability and the impact of the wind tunnel sting on longitudinal stability. Participants were invited to generate solutions using two workshop-provided series of structured overset and unstructured grids, in addition to any participant custom grids of interest. Total and component-level breakdowns for the force and moment coefficients for each test case are presented, as well as sectional pressure distribution data on the wing and tail components, to assess the agreement between several different Reynolds-averaged Navier-Stokes CFD solvers.
I worked on two projects during my summer internship at Sandia. My official title was “Intern - Mission Tech Electrical Eng./Computer Eng.- R&D Undergraduate Summer.” I worked at the central location, which is Albuquerque, New Mexico. The department you are placed in at Sandia doesn’t always correspond to the people you will be working with. For example, I only directly worked with one person from my department this summer. On one of my projects, I worked with a diverse team of engineers from many different departments. On my other project, I mainly worked with two departments, as the project had two distinct parts. As mentioned earlier, I worked on two projects during my summer at Sandia. The first project focused on a lightweight embedded controller in an advanced FPGA System-on-Chip for radar signal processing applications. The term “controller” refers to a hardware device that directs the flow of data between two entities. An FPGA is a reprogrammable integrated circuit (as opposed to an integrated circuit with one purpose). An FPGA was used on this project so in order to protype various ideas for our System-on-Chip. My role on the project was to implement designs on the fabric of the FPGA and design a state machine (written in C) for the processor. My second project was also heavily involved with embedded systems but had a different application. It focused on using a Newton-Raphson control algorithm to stabilize an inverted pendulum using a novel microcontroller. The pendulum dynamics were derived, and it was successfully simulated in MATLAB. I worked on integrating the microcontroller with the inverted pendulum machinery, and converting the Newton-Raphson control algorithm from MATLAB into C. The inverted pendulum was successfully stabilized using a simple PID controller and industry-standard microcontroller. The project is still ongoing, and the team is gearing up for more tests using the novel Newton-Raphson control algorithm and novel microcontroller
Control-configured vehicle technology has increased the demand for detailed analysis of dynamic stability and control, handling and ride qualities, and control system dynamics at the early stages of preliminary design and development. For these early analyses an approximate, but reasonably accurate, set of equations of motion for elastic airplanes is needed. Such a formulation is developed for the lateral dynamics of elastic airplanes. It makes use of rigid-body aerodynamic stability derivatives and the antisymmetric elastic mode shapes and frequencies in formulating the forces and moments due to elastic motion. Verification of accuracy was made by comparison with B-1 airplane dynamics obtained by other methods. Frequencies and damping ratios of the coupled modes agree acceptably well with four antisymmetric elastic modes included.
In order to obtain reliable and accurate values of the stability and control derivatives, the Dryden Fligh Research Center (DFRC) developed a technique for extracting the derivatives from flight data. This technique is implemented by a set of FORTRAN computer programs that is based on a modified maximum likelihood estimator that uses the Newton-Raphson algorithm to perform the required minimization of the derivatives. Data was obtained with a PA-30, light twin-engine general aviation aircraft in zero, half, and full flap configuration in level unaccelerated flight with the landing gear retracted. The derivatives were plotted as functions of angle of attack using various graphical arrangements to show variations of wind tunnel and flight determined values at zero flap settings. Also, data was displayed to show the effects of flap deflection and thrust variation on the longitudinal stability derivatives. The angle of attack and angle of sideslip were measured. The dynamic pressure, velocity, and altitude were calculated, using a FORTRAN computer program, from the static and dynamic pressures. The control deflections of the stabilator, ailerons, and rudder also were recorded along with left throttle position, engine rpm, and manifold pressure.
Abstract Talazoparib (TZ) is a potent poly(ADP-ribose) polymerase 1/2 (PARP1/2) inhibitor that uniquely traps PARP complexes at sites of single-strand DNA damage thereby offering opportunities for targeted radioligand therapy. Radiolabeled halogenated TZ derivatives were synthesized using boronic ester precursors to enable incorporation of diagnostic and therapeutic radionuclides: 18F for PET imaging, 77Br for Auger electron radiotherapy, and 211At for targeted alpha radiotherapy. Copper-mediated radio-halogenation afforded racemic 18F-TZ, 77Br-TZ, and 211At-TZ in sufficient radiochemical yields (4.3 ± 2.6%, n = 33; 29.0 ± 12.0%, n = 4; 3.6 ± 3.8%, n = 9, respectively), ∼99% radiochemical purity and proven stability under formulation conditions. Molecular dynamics simulations of halo-TZ derivatives predicted an inverse relationship between halogen size and PARP1 binding affinity. Indeed, cell uptake of radio-halogenated TZ analogues indicated selective uptake in a panel of cell types that correlated with PARP1 levels but was inversely related to the atomic radii of the halogen series. Despite modest specific activity and specific uptake, 77Br-TZ showed significant cytotoxicity. Further investigation of 18F-TZ with 77Br-TZ as a radiotheranostic pair will be facilitated by the synthetic schemes herein.
A maximum-likelihood output-error parameter estimation technique has been used to obtain stability and control derivatives for the NASA F-18B Systems Research Aircraft. This work has been performed to support flight testing of the active aeroelastic wing (AAW) F-18A project. The goal of this research is to obtain baseline F-18 stability and control derivatives that will form the foundation of the aerodynamic model for the AAW aircraft configuration. Flight data have been obtained at Mach numbers between 0.85 and 1.30 and at dynamic pressures ranging between 600 and 1500 lbf/sq ft. At each test condition, longitudinal and lateral-directional doublets have been performed using an automated onboard excitation system. The doublet maneuver consists of a series of single-surface inputs so that individual control-surface motions cannot be correlated with other control-surface motions. Flight test results have shown that several stability and control derivatives are significantly different than prescribed by the F-18B aerodynamic model. This report defines the parameter estimation technique used, presents stability and control derivative results, compares the results with predictions based on the current F-18B aerodynamic model, and shows improvements to the nonlinear simulation using updated derivatives from this research.
Several problems were studied using two completely different approaches. The initial method was to use the standard linearized perturbation theory by finding the value of the individual small disturbance quantities based on the equations of motion. These were serially eliminated from the equations of motion to derive a single equation that governs the stability of fluid dynamic system. These equations could not be reduced unless the steady state variable depends only on one coordinate. The stability equation based on one dependent variable was found and was examined to determine the stability of a compressible swirling jet. The second method applied a Lagrangian approach to the problem. Since the equations developed were based on different assumptions, the condition of stability was compared only for the Rayleigh problem of a swirling flow, both examples reduce to the Rayleigh criterion. This technique allows including the viscous shear terms which is not possible in the first method. The same problem was then examined to see what effect shear has on stability.
Launch vehicles frequently experience a reduced stability margin through the transonic Mach number range. This reduced stability margin is caused by an undamping of the aerodynamics in one of the lower frequency flexible or rigid body modes. Analysis of the behavior of a flexible vehicle is routinely performed with quasi-steady aerodynamic lineloads derived from steady rigid computational fluid dynamics (CFD). However, a quasi-steady aeroelastic stability analysis can be unconservative at the critical Mach numbers where experiment or unsteady computational aeroelastic (CAE) analysis show a reduced or even negative aerodynamic damping. This paper will present a method of enhancing the quasi-steady aeroelastic stability analysis of a launch vehicle with unsteady aerodynamics. The enhanced formulation uses unsteady CFD to compute the response of selected lower frequency modes. The response is contained in a time history of the vehicle lineloads. A proper orthogonal decomposition of the unsteady aerodynamic lineload response is used to reduce the scale of data volume and system identification is used to derive the aerodynamic stiffness, damping and mass matrices. The results of the enhanced quasi-static aeroelastic stability analysis are compared with the damping and frequency computed from unsteady CAE analysis and from a quasi-steady analysis. The results show that incorporating unsteady aerodynamics in this way brings the enhanced quasi-steady aeroelastic stability analysis into close agreement with the unsteady CAE analysis.
The stability and control of a high-performance aircraft was analyzed, and a design methodology for a departure prevention stability augmentation system (DPSAS) was developed. A general linear aircraft model was derived which includes maneuvering flight effects and trim calculation procedures for investigating highly dynamic trajectories. The stability and control analysis systematically explored the effects of flight condition and angular motion, as well as the stability of typical air combat trajectories. The effects of configuration variation also were examined.
A method is presented for adaptively tuning feedback control gains in a ight control sys- tem to achieve desired closed-loop performance. The method combines efficient parameter estimation for identifying closed-loop dynamics models, with online nonlinear optimization for sequentially perturbing and updating control gains to improve performance. Prior in- formation on stability and control derivatives is not needed, nor is any knowledge about the control system architecture. Following convergence, the optimized control gains (with uncertainties), the open-loop dynamics model, and the closed-loop dynamics model are available. The method is demonstrated for tuning a longitudinal stability augmentation system using a realistic nonlinear ight dynamics simulation of the NASA FASER airplane. Convergence was attained using five piloted maneuvers that spanned approximately one minute of ight test time. Although demonstrated for a relatively simple case, the method is general and can be applied to other aircraft, axes, performance metrics, and control systems.
Abstract Networks with memristive devices are a potential basis for the next generation of computing devices. They are also an important model system for basic science, from modeling nanoscale conductivity to providing insight into the information-processing of neurons. The resistance in a memristive device depends on the history of the applied bias and thus displays a type of memory. The interplay of this memory with the dynamic properties of the network can give rise to new behavior, offering many fascinating theoretical challenges. But methods to analyze general memristive circuits are not well described in the literature. In this paper we develop a general circuit analysis for networks that combine memristive devices alongside resistors, capacitors and inductors and under various types of control. We derive equations of motion for the memory parameters of these circuits and describe the conditions for which a network should display properties characteristic of a resonator system. For the case of a purely memresistive network, we derive Lyapunov functions, which can be used to study the stability of the network dynamics. Surprisingly, analysis of the Lyapunov functions show that these circuits do not always have a stable equilibrium in the case of nonlinear resistance and window functions. The Lyapunov function allows us to study circuit invariances, wherein different circuits give rise to similar equations of motion, which manifest through a gauge freedom and node permutations. Finally, we identify the relation between the graph Laplacian and the operators governing the dynamics of memristor networks operators, and we use these tools to study the correlations between distant memristive devices through the effective resistance.