Approximate corrections for the effects of compressibility on the subsonic stability derivatives of swept wings
Explore the source record for details and available documents.
LIFT CURVES - SLOPE↗
SEARCH · Search NASA
Results for “Stability in control theory”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Theoretical damping in roll and rolling effectiveness of slender cruciform wings
Explore the source record for details and available documents.
CONTROL, LATERAL↗
Experimental Testing of Advanced Generalized Predictive Control for Stability Augmentation and Vibration Reduction of Tiltrotor Aircraft
Generalized Predictive Control (GPC) is an advanced form of an adaptive control algorithm that uses experimentally acquired data to determine the input-output relationship of complex systems through a process called system identification (system ID). GPC has historically been applied to wind tunnel tests of dynamically-scaled tiltrotor aircraft for stability augmentation and vibration reduction since the complex nature of these dynamic systems does not lend itself well to traditional control theory. Advanced GPC (AGPC) improves upon traditional GPC by enabling self-adaptation as conditions change from those used to acquire the system ID and controller performance would normally erode. The present research expands upon previous analytical development and demonstration of AGPC with experimental demonstration. To support AGPC, this present work also identifies and describes figures of merit that define a good working controller and quantifies the uniqueness of the control inputs and quality of the system ID parameters. The present research demonstrates that AGPC consistently performs better than traditional GPC and can successfully adapt to changing conditions.
Active Controls↗
Experimental Testing of Advanced Generalized Predictive Control for Stability Augmentation and Vibration Reduction of Tiltrotor Aircraft
Generalized Predictive Control (GPC) is an advanced form of an adaptive control algorithm that uses experimentally acquired data to determine the input-output relationship of complex systems through a process called system identification (system ID). GPC has historically been applied to wind tunnel tests of dynamically-scaled tiltrotor aircraft for stability augmentation and vibration reduction since the complex nature of these dynamic systems does not lend itself well to traditional control theory. Advanced GPC (AGPC) improves upon traditional GPC by enabling self-adaptation as conditions change from those used to acquire the system ID and controller performance would normally erode. The present research expands upon previous analytical development and demonstration of AGPC with experimental demonstration. To support AGPC, this present work also identifies and describes figures of merit that define a good working controller and quantifies the uniqueness of the control inputs and quality of the system ID parameters. The present research demonstrates that AGPC consistently performs better than traditional GPC and can successfully adapt to changing conditions.
Active Controls↗
Application of linear stability theory in laminar flow design
The linear stability of fully three-dimensional supersonic boundary layers formed over swept-wing configurations is investigated using a modified version of the linear stability code COSAL. Configurations studied include a highly swept leading-edge model to be utilized for transition studies in the LARC Low-disturbance Mach 3.5 Pilot Tunnel. The model is a representation of the leading edge of a laminar flow control wing for the F-16XL aircraft. In addition, the region over a laminar flow control glove fitted on the midportion of an F-16XL wing was studied. For each configuration, estimates of the location of the onset of transition were computed using linear stability theory and the e exp N method. The effectiveness of suction in stabilizing the boundary layer over the F-16XL wing glove was also investigated.
Iyer, Venkit↗
Artificial neural network implementation of a near-ideal error prediction controller
A theory has been developed at the University of Virginia which explains the effects of including an ideal predictor in the forward loop of a linear error-sampled system. It has been shown that the presence of this ideal predictor tends to stabilize the class of systems considered. A prediction controller is merely a system which anticipates a signal or part of a signal before it actually occurs. It is understood that an exact prediction controller is physically unrealizable. However, in systems where the input tends to be repetitive or limited, (i.e., not random) near ideal prediction is possible. In order for the controller to act as a stability compensator, the predictor must be designed in a way that allows it to learn the expected error response of the system. In this way, an unstable system will become stable by including the predicted error in the system transfer function. Previous and current prediction controller include pattern recognition developments and fast-time simulation which are applicable to the analysis of linear sampled data type systems. The use of pattern recognition techniques, along with a template matching scheme, has been proposed as one realizable type of near-ideal prediction. Since many, if not most, systems are repeatedly subjected to similar inputs, it was proposed that an adaptive mechanism be used to 'learn' the correct predicted error response. Once the system has learned the response of all the expected inputs, it is necessary only to recognize the type of input with a template matching mechanism and then to use the correct predicted error to drive the system. Suggested here is an alternate approach to the realization of a near-ideal error prediction controller, one designed using Neural Networks. Neural Networks are good at recognizing patterns such as system responses, and the back-propagation architecture makes use of a template matching scheme. In using this type of error prediction, it is assumed that the system error responses be known for a particular input and modeled plant. These responses are used in the error prediction controller. An analysis was done on the general dynamic behavior that results from including a digital error predictor in a control loop and these were compared to those including the near-ideal Neural Network error predictor. This analysis was done for a second and third order system.
Mcvey, Eugene S.↗
The status of stability theory for deterministic systems.
Dynamic system stability, developments, application and literature
SYSTEM STABILITY↗
Mechanistic Investigation of Molybdenum Disulfide Defect Photoluminescence Quenching by Adsorbed Metallophthalocyanines
Lattice defects play an important role in determining the optical and electrical properties of monolayer semiconductors such as MoS 2 . Although the structures of various defects in monolayer MoS 2 are well studied, little is known about the nature of the fluorescent defect species and their interaction with molecular adsorbates. In this study, the quenching of the low-temperature defect photoluminescence (PL) in MoS 2 is investigated following the deposition of metallophthalocyanines (MPcs). The quenching is found to significantly depend on the identity of the phthalocyanine metal, with the quenching efficiency decreasing in the order CoPc > CuPc > ZnPc, and almost no quenching by metal-free H 2 Pc is observed. Futher, time-correlated single photon counting (TCSPC) measurements corroborate the observed trend, indicating a decrease in the defect PL lifetime upon MPc adsorption, and the gate voltage-dependent PL reveals the suppression of the defect emission even at large Fermi level shifts. Density functional theory modeling argues that the MPc complexes stabilize dark negatively charged defects over luminescent neutral defects through an electrostatic local gating effect. These results demonstrate the control of defectbased excited-state decay pathways via molecular electronic structure tuning, which has broad implications for the design of mixeddimensional optoelectronic devices.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Design aspects of zeppelin operations from case histories
Some widely held beliefs concerning the practicability of rigid airships in air carrier operations are discussed. It is shown by a review of past operational experience, and some basic aerostatic theory, their actual record and the reasons for their demise. Problems of atmospheric density and temperature variations, meteorological factors, aerodynamic stability and control, and mooring difficulties are discussed and related to actual case histories. Structural and flight efficiencies are compared to airplane efficiencies for airplanes contemporary with the zeppelin as well as modern designs. The difficulty of supporting new, commercial airship developments on an economic basis is made clear.
Maiersperger, W. P.↗
Proceedings of the Workshop on Applications of Distributed System Theory to the Control of Large Space Structures
Two general themes in the control of large space structures are addressed: control theory for distributed parameter systems and distributed control for systems requiring spatially-distributed multipoint sensing and actuation. Topics include modeling and control, stabilization, and estimation and identification.
Rodriguez, G.↗
Robust H infinity control design for the space station with structured parameter uncertainty
A robust H-infinity control design methodology and its application to a Space Station attitude and momentum control problem are presented. This new approach incorporates nonlinear multi-parameter variations in the state-space formulation of H-infinity control theory. An application of this robust H-infinity control synthesis technique to the Space Station control problem yields a remarkable result in stability robustness with respect to the moments-of-inertia variation of about 73% in one of the structured uncertainty directions. The performance and stability of this new robust H-infinity controller for the Space Station are compared to those of other controllers designed using a standard linear-quadratic-regulator synthesis technique.
Byun, Kuk-Whan↗
Analytical Approach Validation for the Spin-Stabilized Satellite Attitude
An analytical approach for spin-stabilized spacecraft attitude prediction is presented for the influence of the residual magnetic torques and the satellite in an elliptical orbit. Assuming a quadripole model for the Earth s magnetic field, an analytical averaging method is applied to obtain the mean residual torque in every orbital period. The orbit mean anomaly is used to compute the average components of residual torque in the spacecraft body frame reference system. The theory is developed for time variations in the orbital elements, giving rise to many curvature integrals. It is observed that the residual magnetic torque does not have component along the spin axis. The inclusion of this torque on the rotational motion differential equations of a spin stabilized spacecraft yields conditions to derive an analytical solution. The solution shows that the residual torque does not affect the spin velocity magnitude, contributing only for the precession and the drift of the spin axis of the spacecraft. The theory developed has been applied to the Brazilian s spin stabilized satellites, which are quite appropriated for verification and comparison of the theory with the data generated and processed by the Satellite Control Center of Brazil National Research Institute. The results show the period that the analytical solution can be used to the attitude propagation, within the dispersion range of the attitude determination system performance of Satellite Control Center of Brazil National Research Institute.
Zanardi, Maria Cecilia F. P. S.↗
Approximation in control of flexible structures, theory and application
The sense in which the feedback control law based on an approximate finite dimensional model of a continuous structure approximates a control law which is optimal for the distributed, or infinite dimensional, model of the structure is studied. From the analysis of the various control and stability issues associated with this basis question, useful information for designing finite dimensional compensators which produce near-optimal performance in infinite dimensional systems is gained. Some of the important predictions that can be made about large-order finite dimensional control laws, using the theory of infinite dimensional Riccati equations are indicated.
Gibson, J. S.↗
Experimental Verification of the Rudder-free Stability Theory for an Airplane Model Equipped with a Rudder Having Positive Floating Tendencies and Various Amounts of Friction
Explore the source record for details and available documents.
RUDDERS, BALANCED↗
Design of reduced-order controllers for large flexible space structures
Several approaches to the design of reduced-order controllers for large space structures are discussed. The approaches are based on linear-quadratic-Gaussian (LQG) control theory and include truncation, singular perturbation regulator and estimator, direct sensor feedback, higher-order estimator, and selective suppression of some of the uncontrolled or 'residual' modes. Numerical results are given for a long free-free beam. Sufficient conditions for stability in the presence of control and observation spillovers are outlined. It is shown that the system considered can be satisfactorily controlled using a single torque generator and one attitude and one rate sensor.
Joshi, S. M.↗
Robust Control of Wave Energy Converters Using Unstructured Uncertainty
In the design of ocean wave energy converters, proper control design is essential to the maximization of the power generation performance for the device. However, in realistic applications, this control design must be undertaken in the presence of model uncertainty. This paper considers the use of robust control theory to optimize the nominal performance for a wave energy converter in stochastic waves, subject to the constraint that the controller be stability-robust to unstructured uncertainties. We formulate the problem as a multi-objective optimal control problem, in which the primary objective is the maximization of power generation for the nominal system, and the competing objective is the norm of the uncertainty input/output channel. This optimal control problem is nonconvex, and we therefore propose an iterative algorithm that can be used to arrive at a local optimal solution. This iterative approach employs the concept of Iterative Convex Overbounding, in the context of the classical Method of Centers. Here, the methodology is demonstrated on a model of a single, buoy- type wave energy converter.
16 TIDAL AND WAVE POWER↗
Discrete time domain modelling and analysis of dc-dc converters with continuous and discontinuous inductor current
Using discrete time state variable representation, a generalized computer-aided modeling and analysis of dc-dc converters is presented. The methodology provides exact modeling and is applicable to all types of power stages and duty-cycle control, including continuous and discontinuous inductor current operation. Converter stability, transient behavior and audio susceptibility can be analytically evaluated and predicted. The generalized theory of the proposed approach to converter modeling and analysis is presented first, followed by a demonstrative example applying the theory to a constant frequency buck converter operating in continuous and discontinuous inductor current mode. Excellent agreement with laboratory test data has been observed.
Iwens, R. P.↗
New Directions in Asymptotically Stable Finite-dimensional Adaptive Control of Linear Distributed Parameter Systems
Distributed Parameter Systems (DPS), such as systems described by partial differential equations, require infinite-dimensional state space descriptions to correctly model their dynamical behavior. However, any adaptive control algorithm must be finite-dimensional in order to be implemented via on-line digital computers. Finite-dimensional adaptive control of linear DPS requires stability analysis of nonlinear, time-varying, infinite-dimensional systems. The structure of nonadaptive finite-dimensional control of linear DPS is summarized as it relates to the existence of limiting systems for adaptive control. Two candidate schemes for finite-dimensional adaptive control of DPS are described and critical issues in infinite-dimensional stability analysis are discussed, in particular, the invariance principle, center manifold theory, and relationships between input-output and internal stability.
Balas, M. J.↗