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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.

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At least 1,783 records · Page 99
All sourcesNASA NTRSDOE OSTI
NASA NTRS1982

Model reference adaptive control for linear time varying and nonlinear systems

Model reference adaptive control is applied to linear time varying systems and to nonlinear systems amenable to virtual linearization. Asymptotic stability is guaranteed even if the perfect model following conditions do not hold, provided that some sufficient conditions are satisfied. Simulations show the scheme to be capable of effectively controlling certain nonlinear systems.

Abida, L.↗
DOE OSTI2018

Linear servomotor probe drive system with real-time self-adaptive position control for the Alcator C-Mod tokamak

A new servomotor drive system has been developed for the horizontal reciprocating probe on the Alcator C-Mod tokamak. Real-time measurements of plasma temperature and density—through use of a mirror Langmuir probe bias system—combined with a commercial linear servomotor and controller enables self-adaptive position control. Probe surface temperature and its rate of change are computed in real time and used to control probe insertion depth. It is found that a universal trigger threshold can be defined in terms of these two parameters; if the probe is triggered to retract when crossing the trigger threshold, it will reach the same ultimate surface temperature, independent of velocity, acceleration, or scrape-off layer heat flux scale length. In addition to controlling the probe motion, the controller is used to monitor and control all aspects of the integrated probe drive system.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Linear servomotor probe drive system with real-time self-adaptive position control for the Alcator C-Mod tokamak

A new servomotor drive system has been developed for the horizontal reciprocating probe on the Alcator C-Mod tokamak. Real-time measurements of plasma temperature and density—through use of a mirror Langmuir probe bias system—combined with a commercial linear servomotor and controller enable self-adaptive position control. Probe surface temperature and its rate of change are computed in real time and used to control probe insertion depth. It is found that a universal trigger threshold can be defined in terms of these two parameters; if the probe is triggered to retract when crossing the trigger threshold, it will reach the same ultimate surface temperature, independent of velocity, acceleration, or scrape-off layer heat flux scale length. Finally, in addition to controlling the probe motion, the controller is used to monitor and control all aspects of the integrated probe drive system.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2004

Stochastic Stability of Sampled Data Systems with a Jump Linear Controller

In this paper an equivalence between the stochastic stability of a sampled-data system and its associated discrete-time representation is established. The sampled-data system consists of a deterministic, linear, time-invariant, continuous-time plant and a stochastic, linear, time-invariant, discrete-time, jump linear controller. The jump linear controller models computer systems and communication networks that are subject to stochastic upsets or disruptions. This sampled-data model has been used in the analysis and design of fault-tolerant systems and computer-control systems with random communication delays without taking into account the inter-sample response. This paper shows that the known equivalence between the stability of a deterministic sampled-data system and the associated discrete-time representation holds even in a stochastic framework.

Gonzalez, Oscar R.↗
NASA NTRS1972

A graphical test for checking the stability of a linear time-invariant feedback system.

A continuous-time scalar linear time-invariant feedback system is considered for the purpose of checking Willems' (1969, 1970) graphical test for a scalar linear time-invariant feedback system with constant feedback. Heavy reliance is placed on the theory of almost periodic functions. Following definition of the problem and layout of notation, attention is given to solution of the problem, considering only the almost periodic part of the open-loop transfer function.

Callier, F. M.↗
NASA NTRS2006

Parameter and Structure Inference for Nonlinear Dynamical Systems

A great many systems can be modeled in the non-linear dynamical systems framework, as x = f(x) + xi(t), where f() is the potential function for the system, and xi is the excitation noise. Modeling the potential using a set of basis functions, we derive the posterior for the basis coefficients. A more challenging problem is to determine the set of basis functions that are required to model a particular system. We show that using the Bayesian Information Criteria (BIC) to rank models, and the beam search technique, that we can accurately determine the structure of simple non-linear dynamical system models, and the structure of the coupling between non-linear dynamical systems where the individual systems are known. This last case has important ecological applications.

Morris, Robin D.↗
NASA NTRS1980

System identification of large space structures

The paper deals with the problem of system identifiability for a linear dynamical system. Two theorems are given relating the sufficient condition of system identifiability for certain linear structures to the total number of inputs and outputs. The principle of least squares, that seeks the minimization of a cost function is employed to carry out the system identification process. To illustrate the concept of the paper, a structural model of a beam with point masses is examined. Parameter identification methods are studied and a random search technique is introduced.

Juang, J. N.↗
DOE OSTI2011

Designing a Stochastic Adaptive Impulsive Observer for Stochastic Linear and Nonlinear Impulsive Systems

State observation (estimation) is a very important issue in system analysis and control. This paper develops a new observer called Stochastic Adaptive Impulsive Observer (SAIO) for the state estimation of impulsive systems. The proposed observer is applicable to linear and nonlinear stochastic impulsive systems. In addition, the effect of parametric uncertainty is considered and unknown parameters of the system are estimated by suitable adaptation laws. Impulsive system theory, particularly stochastic Lyapunov-like function, is used to analyze the stability and convergence of the state estimations. The main advantages of the proposed observer are: 1) it gives continuous estimation from discrete time measurements of the system output, and 2) it is useful for state estimation when continuous measurements are impossible or expensive. Simulation results show the effectiveness of the proposed observer and we believe that it has many applications in control and estimation theories.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗