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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRS1972

On practical stability.

In this paper, a class of nonlinear nonautonomous systems with multiple nonlinearities is considered. Sufficient conditions are developed for a type of practical stability with specified settling time. The conditions are independent of the actual form of nonlinear characteristics so that they can be interpreted as conditions for 'absolute' practical stability. The stability test is reduced to verification of the Hurwitz property of a constant matrix. This makes the stability analysis of the considered class of nonlinear systems convenient for machine computations. The proposed practical stability analysis is applied to a third-order system with several nonlinearities.

Grujic, L. T.↗
NASA NTRS1982

Rotor vibration caused by external excitation and rub

For turbomachinery with low natural frequencies, considerations have been recently required for rotor vibrations caused by external forces except unbalance one, such as foundation motion, seismic wave, rub and so forth. Such a forced vibration is investigated analytically and experimentally in the present paper. Vibrations in a rotor-bearing system under a harmonic excitation are analyzed by the modal technique in the case of a linear system including gyroscopic effect. For a nonlinear system a new and powerful quasi-modal technique is developed and applied to the vibration caused by rub.

Matsushita, O.↗
NASA NTRS1988

Technology advances for Space Shuttle processing

One of the major initial tasks of the Space Systems Integration and Operations Research Applications (SIORA) Program was the application of automation and robotics technology to all aspects of the Shuttle tile processing and inspection system. The SIORA Program selected a nonlinear systems engineering methodology which emphasizes a team approach for defining, developing, and evaluating new concepts and technologies for the operational system. This is achieved by utilizing rapid prototyping testbeds whereby the concepts and technologies can be iteratively tested and evaluated by the team. The present methodology has clear advantages for the design of large complex systems as well as for the upgrading and evolution of existing systems.

Wiskerchen, M. J.↗
NASA NTRS1998

Control of the NASA Langley 16-Foot Transonic Tunnel with the Self-Organizing Feature Map

A predictive, multiple model control strategy is developed based on an ensemble of local linear models of the nonlinear system dynamics for a transonic wind tunnel. The local linear models are estimated directly from the weights of a Self Organizing Feature Map (SOFM). Local linear modeling of nonlinear autonomous systems with the SOFM is extended to a control framework where the modeled system is nonautonomous, driven by an exogenous input. This extension to a control framework is based on the consideration of a finite number of subregions in the control space. Multiple self organizing feature maps collectively model the global response of the wind tunnel to a finite set of representative prototype controls. These prototype controls partition the control space and incorporate experimental knowledge gained from decades of operation. Each SOFM models the combination of the tunnel with one of the representative controls, over the entire range of operation. The SOFM based linear models are used to predict the tunnel response to a larger family of control sequences which are clustered on the representative prototypes. The control sequence which corresponds to the prediction that best satisfies the requirements on the system output is applied as the external driving signal. Each SOFM provides a codebook representation of the tunnel dynamics corresponding to a prototype control. Different dynamic regimes are organized into topological neighborhoods where the adjacent entries in the codebook represent the minimization of a similarity metric which is the essence of the self organizing feature of the map. Thus, the SOFM is additionally employed to identify the local dynamical regime, and consequently implements a switching scheme than selects the best available model for the applied control. Experimental results of controlling the wind tunnel, with the proposed method, during operational runs where strict research requirements on the control of the Mach number were met, are presented. Comparison to similar runs under the same conditions with the tunnel controlled by either the existing controller or an expert operator indicate the superiority of the method.

Motter, Mark A.↗
NASA NTRS1982

Gain optimization with nonlinear controls

An algorithm has been developed for the analysis and design of controls for nonlinear systems. The technical approach is to use statistical linearization to model the nonlinear dynamics of a system. A covariance analysis is performed to determine the behavior of the dynamical system and a quadratic cost function. Expressions for the cost function and its derivatives are determined so that numerical optimization techniques can be applied to determine optimal feedback laws. The primary application for this report is centered about the design of controls for nominally linear systems but where the controls are saturated or limited by fixed constraints. The analysis is general however and numerical computation requires only that the specific nonlinearity be considered in the analysis.

Slater, G. L.↗
NASA NTRS1987

Nonlinear plants, factorizations and stable feedback systems

For nonlinear plants represented by causal maps defined over extended spaces, right factorization and normalized right-coprime factorization concepts are discussed in terms of well-posed stable feedback systems. This setup covers continuous-time, discrete-time, time-invariant or time-varying input-output maps. The nonlinear maps are factored in terms of causal bounded-input bounded-output stable maps. In factored form, all instabilities of the original map are represented by the inverse of a causal stable `denominator' map. The existence of maps with right factorizations and normalized right-coprime factorizations is shown using a well-posed stable unity-feedback system. In the case where one of the subsystems has a normalized right-coprime factorization, the stability of the feedback system is equivalent to the stability of the pseudostate map.

Desoer, Charles A.↗
NASA NTRS1964

Statistical communication theory

Generalization of superposition principle of statistical communication theory & investigation of class of nonlinear systems

STATISTICAL COMMUNICATION THEORY↗
NASA NTRS1989

Application of numerical optimization techniques to control system design for nonlinear dynamic models of aircraft

Control system design for general nonlinear flight dynamic models is considered through numerical simulation. The design is accomplished through a numerical optimizer coupled with analysis of flight dynamic equations. The general flight dynamic equations are numerically integrated and dynamic characteristics are then identified from the dynamic response. The design variables are determined iteratively by the optimizer to optimize a prescribed objective function which is related to desired dynamic characteristics. Generality of the method allows nonlinear effects to aerodynamics and dynamic coupling to be considered in the design process. To demonstrate the method, nonlinear simulation models for an F-5A and an F-16 configurations are used to design dampers to satisfy specifications on flying qualities and control systems to prevent departure. The results indicate that the present method is simple in formulation and effective in satisfying the design objectives.

Lan, C. Edward↗
NASA NTRS1991

A system identification model for adaptive nonlinear control

A system identification model that combines generalized-spline function approximation with a nonlinear control system is described. The complete control system contains three main elements: a nonlinear-inverse-dynamic control law that depends on a comprehensive model of the plant, a state estimator whose outputs drive the control law, and a function approximation scheme that models the system dynamics. The system-identification task, which combines an extended Kalman filter with a function approximator modeled as an artificial neural network, is considered. The results of an application of the identification techniques to a nonlinear transport aircraft model are presented.

Linse, Dennis J.↗