The application of specific optimal control to the design of desensitized model following control systems
Desensitized linear servo model following feedback control systems design using specific optimal control concepts
Roy, R. J.↗
SEARCH · Engineering Papers
Results for “linear systems”
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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Design of linear and nonlinear control systems via state variable feedback, with applications in nuclear reactor control
Linear and nonlinear control systems via state variable feedback with applications in nuclear reactor control
LINEAR SYSTEM↗
Decentrally stabilizable linear and bilinear large-scale systems
Two classes of large-scale systems are identified, which can always be stabilized by decentralized feedback control. For the class of systems composed of interconnected linear subsystems, we can choose local controllers for the subsystems to achieve stability of the overall system. The same linear feedback scheme can be used to stabilize a class of linear systems with bilinear interconnections. In this case, however, the scheme is used to establish a finite region of stability for the overall system. The stabilization algorithm is applied to the design of a control system for the Large-Space Telescope.
Siljak, D. D.↗
Digital system identification and its application to digital flight control
On-line system identification of linear discrete systems for implementation in a digital adaptive flight controller is considered by the conventional extended Kalman filter and a decoupling process in which the linear state estimation problem and the linear parameter identification problem are each treated separately and alternately. Input requirements for parameter identifiability are established using the standard conditions of observability for a time variant system. Experimental results for simulated linearized lateral aircraft motion are included along with the effect of different initialization and updating procedures for the priming trajectory used by the filter.
Kotob, S.↗
Fundamental Concepts of Stability Theory
Theorems and definitions for generation of Liapunov functions for analysis of linear and nonlinear dynamic systems
LIAPUNOV FUNCTION↗
On the optimal control of a system governed by a linear parabolic equation with white noise inputs.
Optimal control of system governed by linear parabolic equation with white noise inputs, using mathematical model to generate distributed system analog
Kushner, H. J.↗
Stability of linear time-invariant systems.
Stability conditions for multiple input-output linear time invariant feedback systems, noting open loop system impulse response characteristics
Desoer, C. A.↗
Method and system for non-linear motion estimation
A method and system for extrapolating and interpolating a visual signal including determining a first motion vector between a first pixel position in a first image to a second pixel position in a second image, determining a second motion vector between the second pixel position in the second image and a third pixel position in a third image, determining a third motion vector between one of the first pixel position in the first image and the second pixel position in the second image, and the second pixel position in the second image and the third pixel position in the third image using a non-linear model, determining a position of the fourth pixel in a fourth image based upon the third motion vector.
Lu, Ligang↗
Theoretical Development of Controller Transfer applied to Dynamical Systems
Data-driven control strategies suffer from the necessity of training and its associated computational time and cost. This motivates the continuous increase of popularity of transfer learning based methods. In this paper, we have investigated transfer learning in the context of controller for dynamical systems. First, we have derived conditions under which controller can be transferred between two linear dynamical systems. Furthermore, we have introduced a novel algorithm to design the transferable and non-transferable control components for linear systems. Secondly, we have derived conditions under which a stabilizing controller can be transferred between two different nonlinear dynamical systems. Furthermore, we have used the notion of zero dynamics to transform the nonlinear dynamics into global normal form, to derive the transferability conditions on the controller. Finally, we have numerically evaluated the performance of our transfer learning based methods for two sets of example linear and nonlinear dynamical systems.
Chakraborty, Indrasis↗
Rigorous justification for the space–split sensitivity algorithm to compute linear response in Anosov systems
Ruelle gave a formula for linear response of transitive Anosov diffeomorphisms. Recently, practically computable realizations of Ruelle's formula have emerged that potentially enable sensitivity analysis of certain high-dimensional chaotic numerical simulations encountered in the applied sciences. In this paper, we provide full mathematical justification for the convergence of one such efficient computation, the space–split sensitivity, or S3, algorithm. In S3, Ruelle's formula is computed as a sum of two terms obtained by decomposing the perturbation vector field into a coboundary and a remainder that is parallel to the unstable direction. Such a decomposition results in a splitting of Ruelle's formula that is amenable to efficient computation. Here, we prove the existence of the S3 decomposition and the convergence of the computations of both resulting components of Ruelle's formula.
97 MATHEMATICS AND COMPUTING↗
Truncated non-linear interferometer-based sensor system
A truncated non-linear interferometer-based sensor system includes an input that receives an optical beam and a non-linear amplifier that generates a probe beam and a conjugate beam from the optical beam. The system's local oscillators are related to the probe beam and the conjugate beam. The system includes a sensor that transduces an input with the probe beam and the conjugate beam. The transduction detects changes in the phase of each of the probe beam and the conjugate beam. The system's phase sensitive detectors detect phase modulations between the respective local oscillators, the probe beam, and the conjugate beam and outputs phase signals based on detected phase modulations. The system measures phase signals indicative of the sensor's input resulting from a sum or difference of the phase signals. The measurement exhibits a quantum noise reduction in an intensity difference, a phase sum, or an amplitude difference quadrature.
47 OTHER INSTRUMENTATION↗
Recursive state estimation - Unknown but bounded errors and system inputs.
State of linear dynamic system using noisy observations with unknown but bounded errors and system inputs, deriving recursive algorithm
Schweppe, F. C.↗
Linear and/or curvilinear rail mount system
One or more linear and/or curvilinear mounting rails are coupled to a structure. Each mounting rail defines a channel and at least one cartridge assembly is engaged in the channel. Each cartridge assembly includes a housing that slides within the channel. The housing defines a curvilinearly-shaped recess longitudinally aligned with the channel when the housing is in engagement therewith. The cartridge assembly also includes a cleat fitted in the recess for sliding engagement therealong. The cleat can be coupled to a fastener that passes through the mounting rail and the housing when the housing is so-engaged in the channel. The cleat is positioned in the recess by a position of the fastener.
Thomas, Jackie D.↗
Stochastic Stability of Nonlinear Sampled Data Systems with a Jump Linear Controller
This paper analyzes the stability of a sampled- data system consisting of a deterministic, nonlinear, time- invariant, continuous-time plant and a stochastic, discrete- time, jump linear controller. The jump linear controller mod- els, for example, computer systems and communication net- works 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. To analyze stability, appropriate topologies are introduced for the signal spaces of the sampled- data system. With these topologies, the ideal sampling and zero-order-hold operators are shown to be measurable maps. This paper shows that the known equivalence between the stability of a deterministic, linear sampled-data system and its associated discrete-time representation as well as between a nonlinear sampled-data system and a linearized representation holds even in a stochastic framework.
Gonzalez, Oscar R.↗
Linear and nonlinear system identification of autonomic heart-rate modulation
No abstract available
NASA Discipline Regulatory Physiology↗
On the optimal control of a system governed by a linear parabolic equation with white noise inputs
Optimum control of system governed by linear parabolic equation with white noise inputs
WHITE NOISE↗
A generalization of the Nyquist stability criterion
This paper presents a generalization of the Nyquist stability criterion to include general multivariable linear stationary systems subject to linear static and dynamic feedback. At the same time, a unifying proof is given for all known versions of the Nyquist criterion for finite dimensional systems.
Stevens, P. K.↗
Transformation matrices between non-linear and linear differential equations
In the linearization of systems of non-linear differential equations, those systems which can be exactly transformed into the second order linear differential equation Y"-AY'-BY=0 where Y, Y', and Y" are n x 1 vectors and A and B are constant n x n matrices of real numbers were considered. The 2n x 2n matrix was used to transform the above matrix equation into the first order matrix equation X' = MX. Specially the matrix M and the conditions which will diagonalize or triangularize M were studied. Transformation matrices P and P sub -1 were used to accomplish this diagonalization or triangularization to return to the solution of the second order matrix differential equation system from the first order system.
Sartain, R. L.↗