Linear digital control.
Linear discrete of digital controller design for optimal regulation of feedback control systems
OPTIMAL CONTROL↗
SEARCH · Engineering Papers
Results for “linear optimization”
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.
Sensitivity reduction using optimally derived controllers
Feedback structures to reduce parameter sensitivity of linear system derived from solution of classical linear regulator problem for design of automatic control systems
AUTOMATIC CONTROL↗
On the separation theorem of stochastic control.
Optimal control and filtering problem for stochastic linear dynamic system reduced to independent equations
Wonham, W. M.↗
Mathematical programming and the control of Markov chains
Linear and dynamic programming and Markov chain optimal control
Kleinman, A. J.↗
A survey of discrete Kalman-Bucy filtering with unknown noise covariances
Discrete Kalman-Bucy linear filtering with inaccurate noise covariances, considering optimal and suboptimal systems, error analysis, probability theory, etc
Weiss, I. M.↗
Necessary conditions for continuous parameter stochastic optimization problems
Abstract variational theory application to continuous parameter stochastic optimization problems to derive maximum principles in linear programming
Kushner, H. J.↗
Optimal inputs for system identification
Identification criteria are presented for linear dynamic systems with and without process noise. With process noise, the state equations are replaced by the Kalman filter equations. If the identification performance index is expanded in a Taylor's series with respect to the parameters to be identified, then maximizing the weighting factor of the quadratic term with respect to the inputs will insure that an identification algorithm will converge more rapidly and to a more accurate result than with nonoptimal inputs. The expectation of this weighting factor is the Fisher information matrix, and its inverse is a lower bound for the covariance of the parameters. Direct and indirect methods of calculating the information matrix are presented for systems with and without process noise.
Reid, D. B.↗
Application of modern control theory to the design of optimum aircraft controllers
A procedure is described for synthesis of optimal aircraft control systems by application of the concepts of optimal control theory to time-invariant linear systems with quadratic performance criteria. Essential in this synthesis procedure is the solution of the Riccati matrix equation which results in a constant linear feedback control law for an output regulator which maintains a plant in an equilibrium in the presence of impulse disturbances. An algorithm is derived for designing maneuverable output regulators with selected state variables for feedback.
Power, L. J.↗
Optimal control theory investigation of proprotor/wing response to vertical gust
Optimal control theory is used to design linear state variable feedback to improve the dynamic characteristics of a rotor and cantilever wing representing the tilting proprotor aircraft in cruise flight. The response to a vertical gust and system damping are used as criteria for the open and closed loop performance. The improvement in the dynamic characteristics achievable is examined for a gimballed rotor and for a hingeless rotor design. Several features of the design process are examined, including: (1) using only the wing or only the rotor dynamics in the control system design; (2) the use of a wing flap as well as the rotor controls for inputs; (3) and the performance of the system designed for one velocity at other forward speeds.
Frick, J. K. D.↗
Programming the gradient projection algorithm
The gradient projection method of numerical optimization which is applied to problems having linear constraints but nonlinear objective functions is described and analyzed. The algorithm is found to be efficient and thorough for small systems, but requires the addition of auxiliary methods and programming for large scale systems with severe nonlinearities. In order to verify the theoretical results a digital computer is used to simulate the algorithm.
Hargrove, A.↗
Issues in modeling and controlling the SCOLE configuration
The parametric study of the in-plane Spacecraft Control Laboratory Experiment (SCOLE) system, the Floquet Stability Analysis, and three dimensional formulations of the SCOLE system dynamics are examined. Control issues are discussed, such as: control of large structures with delayed input in continuous time; control with delayed input in discrete time; control law design for SCOLE using Linear Quadratic Gaussian (LQC)/TRR technique; and optimal torque control for SCOLE slewing maneuvers.
Bainum, Peter M.↗
Neighboring extremal guidance for systems with a piecewise linear control
The neighboring extremal feedback control law is developed for systems with a piecewise linear control for the case where the optimal control is obtained by nonlinear programming techniques. To develop the control perturbation for a given deviation from the nominal path, the second variation is minimized subject to the constraint that the final conditions be satisfied. This process leads to a feedback relationship between the control perturbation and the measured deviation from the nominal state. A simple example, the lunar launch problem, is used to demonstrate the validity of the guidance law. For model errors on the order of 5 percent, the results indicate that 5 percent errors occur in the final conditions.
Hull, David G.↗
Aerodynamic performance optimization of a rotor blade using a neural network as the analysis
This paper describes the use of neural networks as a replacement for rotor analyses in a conventional aerodynamic performance optimization procedure. The optimization procedure minimizes an objective function, a linear combination of horsepower required for hover, forward flight, and maneuver. The design variables are pretwist, taper initiation, taper ratio, and blade root chord. Constraints consist of limits on horsepower required (for hover, forward flight, and maneuver), stall, trim, and minimum tip chord. Neural network analyses agree with conventional analyses.
Lamarsh, William J., II↗
Neighboring suboptimal control
The neighboring extremal feedback control law is developed for systems with a piecewise linear control for the case where the optimal control is obtained by nonlinear programming techniques. To develop the control perturbation for a given deviation from the nominal path, the second variation is minimized subject to the constraint that the final conditions be satisfied. This process leads to a feedback relationship between the control perturbation and the measured deviation from the nominal state.
Hull, David G.↗
A steady-state Kalman filter for assimilating data from a single polar orbiting satellite
A steady-state scheme for data assimilation in the context of a single, short period (relative to a day), sun-synchronous, polar-orbiting satellite is examined. If the satellite takes observations continuously, the gains, which are the weights for blending observations and predictions together, are steady in time. For a linear system forced by random noise, the optimal steady-state gains (Wiener gains) are equivalent to those of a Kalman filter. Computing the Kalman gains increases the computational cost of the model by a large factor, but computing the Wiener gains does not. The latter are computed by iteration using prior estimates of the gains to assimilate simulated observations of one run of the model, termed 'truth' into another run termed 'prediction'. At each stage, the prediction errors form the basis for the next estimate of the gains. Steady state is achieved after three or four iterations. Further simplification is achieved by making the gains depend on longitudinal distance from the observation point, not on absolute longitude. For a single-layer primitive equation model, the scheme works well even if only the mass field is observed but not the velocity field. Although the scheme was developed for Mars Observer, it should be applicable to data retrieved from Earth atmosphere satellites, for example, UARS.
Banfield, Don↗
Structural Optimization for Reliability Using Nonlinear Goal Programming
This report details the development of a reliability based multi-objective design tool for solving structural optimization problems. Based on two different optimization techniques, namely sequential unconstrained minimization and nonlinear goal programming, the developed design method has the capability to take into account the effects of variability on the proposed design through a user specified reliability design criterion. In its sequential unconstrained minimization mode, the developed design tool uses a composite objective function, in conjunction with weight ordered design objectives, in order to take into account conflicting and multiple design criteria. Multiple design criteria of interest including structural weight, load induced stress and deflection, and mechanical reliability. The nonlinear goal programming mode, on the other hand, provides for a design method that eliminates the difficulty of having to define an objective function and constraints, while at the same time has the capability of handling rank ordered design objectives or goals. For simulation purposes the design of a pressure vessel cover plate was undertaken as a test bed for the newly developed design tool. The formulation of this structural optimization problem into sequential unconstrained minimization and goal programming form is presented. The resulting optimization problem was solved using: (i) the linear extended interior penalty function method algorithm; and (ii) Powell's conjugate directions method. Both single and multi-objective numerical test cases are included demonstrating the design tool's capabilities as it applies to this design problem.
El-Sayed, Mohamed E.↗
Pilot Evaluation of Adaptive Control in Motion-Based Flight Simulator
The objective of this work is to assess the strengths, weaknesses, and robustness characteristics of several MRAC (Model-Reference Adaptive Control) based adaptive control technologies garnering interest from the community as a whole. To facilitate this, a control study using piloted and unpiloted simulations to evaluate sensitivities and handling qualities was conducted. The adaptive control technologies under consideration were ALR (Adaptive Loop Recovery), BLS (Bounded Linear Stability), Hybrid Adaptive Control, L1, OCM (Optimal Control Modification), PMRAC (Predictor-based MRAC), and traditional MRAC
Kaneshige, John T.↗
Wavefront Sensing of X-Ray Telescopes
Phase Retrieval analysis of off-axis or defocused focal-plane data from telescope optics has been proven effective in understanding misalignments and optical aberrations in normal incidence telescopes. The approach is used, e.g., in commissioning of the James Webb Space Telescope (JWST) segmented primary mirror. There is a similar need for evaluating low-order figure errors of grazing incidence mirrors and nested telescope assemblies. When implemented in these systems, phase retrieval does not depend on normal incidence access to each mirror (shell) surface and, therefore, provides an effective means for evaluating nested x-ray telescopes during integration and test. We have applied a well-known phase retrieval algorithm to grazing incidence telescopes. The algorithm uses the Levenberg-Marquardt optimization procedure to perform a non-linear least-squares fit of the telescope Point Spread Function (PSF). The algorithm can also retrieve low order figure errors at visible wavelengths where optical diffraction is the dominant defect in the PSF. In this paper we will present the analytical approach and its implementation for grazing incidence mirrors of the International X-Ray Observatory (IXO). We analyze the effects of low order axial surface errors individually, and in combination on the system PSF at 633 nanometers. We demonstrate via modeling that the wavefront sensing algorithm can recover axial errors (of the grazing incidence mirrors) to a small fraction of the known axial figure errors using simulated PSFs as input data to the algorithm.
Saha, Timo↗