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At least 1,657 records · Page 92

Optimal control alleviation of tilting proprotor gust response

Optimal control theory is applied to the design of a control system for alleviation of the gust response of tilting proprotor aircraft. Using a proprotor and cantilever wing analytical model, the uncontrolled and controlled gust response is examined over the entire operating range of the aircraft except for hover: helicopter mode, conversion, and airplane mode flight. Substantial improvements in the loads, ride quality, and aeroelastic stability are possible with a properly designed controller. A single controller, nominally optimal only at the design point speed (160 knots here), operated efficiently over the entire speed range, with the possible exception of very low speed in helicopter mode. Kalman-Bucy filters were used as compensation networks to provide state estimates from various measurements in the wing motion, rotor speed perturbation, and tip-path-plane tilt.

Johnson, W.↗

Development of a digital adaptive optimal linear regulator flight controller

Digital adaptive controllers have been proposed as a means for retaining uniform handling qualities over the flight envelope of a high-performance aircraft. Towards such an implementation, an explicit adaptive controller, which makes direct use of online parameter identification, has been developed and applied to the linearized lateral equations of motion for a typical fighter aircraft. The system is composed of an online weighted least-squares parameter identifier, a Kalman state filter, and a model following control law designed using optimal linear regulator theory. Simulation experiments with realistic measurement noise indicate that the proposed adaptive system has the potential for onboard implementation.

Berry, P.↗

Performance and sensitivity analysis of the generalized likelihood ratio method for failure detection

Results of the generalized likelihood ratio (GLR) technique for the detection of failures in aircraft application are presented, and its relationship to the properties of the Kalman-Bucy filter is examined. Under the assumption that the system is perfectly modeled, the detectability and distinguishability of four failure types are investigated by means of analysis and simulations. Detection of failures is found satisfactory, but problems in identifying correctly the mode of a failure may arise. These issues are closely examined as well as the sensitivity of GLR to modeling errors. The advantages and disadvantages of this technique are discussed, and various modifications are suggested to reduce its limitations in performance and computational complexity.

Bueno, R. A.↗

An implementable digital adaptive flight controller designed using stabilized single stage algorithms

Simple mechanical linkages have not solved the many control problems associated with high performance aircraft maneuvering throughout a wide flight envelope. One procedure for retaining uniform handling qualities over such an envelope is to implement a digital adaptive controller. Towards such an implementation an explicit adaptive controller which makes direct use of on-line parameter identification, has been developed and applied to both linearized and nonlinear equations of motion for a typical fighter aircraft. This controller is composed of an on-line weighted least squares parameter identifier, a Kalman state filter, and a model following control law designed using single stage performance indices. Simulation experiments with realistic measurement noise indicate that the proposed adaptive system has the potential for on-board implementation.

Kaufman, H.↗

Optimal control alleviation of tilting proprotor gust response

Optimal control theory is applied to the design of a control system for alleviation of the gust response of tilting proprotor aircraft. Using a proprotor and cantilever wing analytical model, the uncontrolled and controlled gust response is examined over the entire operating range of the aircraft except for hover: helicopter mode, conversion, and airplane mode flight. Substantial improvements in the loads, ride quality, and aeroelastic stability are possible with a properly designed controller. A single controller, nominally optimal only at the design point speed (160 knots here), operated efficiently over the entire speed range, with the possible exception of very low speed in helicopter mode. Kalman-Bucy filters were used as compensation networks to provide state estimates from various measurements in the system. Efficient control requires the measurement of the wing motion, rotor speed perturbation, and tip-path-plane tilt.

Johnson, W.↗

An implementable digital adaptive flight controller designed using stabilized single-stage algorithms

An explicit adaptive controller, which makes direct use of on-line parameter identification, has been developed and applied to both the linearized and nonlinear equations of motion for the F-8 aircraft. This controller is composed of an on-line weighted least squares parameter identifier, a Kalman state filter, and a real model following control law designed using single-stage performance indices. The corresponding control gains are readily adjustable in accordance with parameter changes to ensure asymptotic stability if the conditions of perfect model following are satisfied, and stability in the sense of boundedness otherwise. Simulation experiments with realistic measurement noise indicate that the controller was effective in compensating for parameter variations and capable of rapid recovery from a set of erroneous initial parameter estimates which defined a set of destabilizing gains.

Alag, G.↗

Digital pointing control

The digital pointing control system developed for the Space Shuttle Data Bus is discussed. The device, which interfaces with NASA standard sensor units, contains a front panel controller, a development system to load, inspect, print, and store the program and data, and a 'test jig' to provide closed-loop controller operation. The system is described with particular reference to the tracker-gyro interfaces, the control algorithms and compensation procedures, Kalman-estimation filtering, the proportional power output, and the discrete output capability. The results of simulation studies are presented and the development status is noted.

Studer, P. A.↗

Towards sub-optimal stochastic control of partially observable stochastic systems

A class of multidimensional stochastic control problems with noisy data and bounded controls encountered in aerospace design is examined. The emphasis is on suboptimal design, the optimality being taken in quadratic mean sense. To that effect the problem is viewed as a stochastic version of the Lurie problem known from nonlinear control theory. The main result is a separation theorem (involving a nonlinear Kalman-like filter) suitable for Lurie-type approximations. The theorem allows for discontinuous characteristics. As a byproduct the existence of strong solutions to a class of non-Lipschitzian stochastic differential equations in dimensions is proven.

Ruzicka, G. J.↗

Modal methods in optimal control synthesis

Efficient algorithms for solving linear smoother-follower problems with quadratic criteria are presented. For time-invariant systems, the algorithm consists of one backward integration of a linear vector equation and one forward integration of another linear vector equation. Furthermore, the backward and forward Riccati matrices can be expressed in terms of the eigenvalues and eigenvectors of the Euler-Lagrange equations. Hence, the gains of the forward and backward Kalman-Bucy filters and of the optimal state-feedback regulator can be determined without integration of matrix Riccati equations. A computer program has been developed, based on this method of determining the gains, to synthesize the optimal time-invariant compensator in the presence of random disturbance inputs and random measurement errors. The program also computes the rms state and control variables of the optimal closed-loop system.

Bryson, A. E., Jr.↗

Venus gravity - A high-resolution map

The Doppler data from the radio tracking of the Pioneer Venus Orbiter (PVO) have been used in a two-stage analysis to develop a high-resolution map of the gravitational potential of Venus, represented by a central mass and a surface mass density. The two-stage procedure invokes a Kalman filter-smoother to determine the orbit of the spacecraft, and a stabilized linear inverter to estimate the surface mass density. The resultant gravity map is highly correlated with the topographic map derived from the PVO radar altimeter data. However, the magnitudes of the gravity variations are smaller than would be expected if the topography were uncompensated, indicating that at least partial compensation has taken place.

Reasenberg, R. D.↗

Towards sub-optimal stochastic control of partially observable stochastic systems

The paper deals with a class of multidimensional stochastic control problems with noisy data and bounded controls encountered in aerospace design. The emphasis is on suboptimal design, the optimality being taken in quadratic mean sense. To that effect the problem is viewed as a stochastic version of the Lurie problem known from nonlinear control theory. The main result is a separation theorem (involving a nonlinear Kalman-like filter) suitable for Lurie-type approximations. The theorem allows for discontinuous characteristics. As a byproduct the existence of strong solutions to a class of non-Lipschitzian stochastic differential equations in n dimensions is proved.

Ruzicka, G. J.↗

Profiling atmospheric water vapor by microwave radiometry

High-altitude microwave radiometric observations at frequencies near 92 and 183.3 GHz were used to study the potential of retrieving atmospheric water vapor profiles over both land and water. An algorithm based on an extended kalman-Bucy filter was implemented and applied for the water vapor retrieval. The results show great promise in atmospheric water vapor profiling by microwave radiometry heretofore not attainable at lower frequencies.

Wang, J. R.↗

Venus gravity west of Beta Regio

Doppler tracking data from the Pioneer Venus Orbiter (PVO) have been used to estimate the anomalous gravity field in the region of Venus west of Beta Regio. The analysis invokes a Kalman filter-smoother to solve the nonlinear spacecraft state estimation problem and a linear Bayesian estimator to perform the geophysical inversion. The topographic map for this region, derived from the PVO radar, has been filtered to have the same distortions and degree of smoothing as the gravity map. The undulations of the gravity are about 0.2 times as large as expected from the topography, on the assumption that the latter is uncompensated. A comparison of the gravity and topography by means of the spectral admittance is consistent with Airy compensation at a depth of 50 km, if the surface material has a density of 2.6 g/cu cm. However, this is not a unique interpretation.

Goldberg, Z. M.↗

Robust state estimation with imperfect sensors

Robustness properties of extended Kalman-type filters are investigated for time-varying plants when nonlinearities or linear dynamics are present at the plant input and output. Sufficient conditions for the asymptotic stability (of the state estimation error) in the absence of noise are obtained when the nonlinearities or the linear dynamics are perfectly known. When the nonlinearities are known only within bands of uncertainty, the estimation error is shown to be ultimately bounded under certain conditions. The results obtained highlight the robustness properties of such filters, which are similar to, but not exact duals of those of linear quadratic regulators.

Joshi, S. M.↗

Spillover stabilization and decentralized modal control of large space structures

The stabilization of the neglected dynamics of the higher modes of vibration in large space structures is studied, and the influence of the structure of the plant noise intensity matrix of the Kalman-Bucy filter on the stability margin of the residual modes is shown. An optimization procedure uses information on the residual modes to minimize spillover of known residual modes while preserving robustness with respect to the unknown dynamics, and the optimum plant noise intensity matrix is selected to maximize the stability margins of the residual modes and to properly place the observer poles. Examples for both centralized and decentralized control are considered.

Czajkowski, Eva A.↗

Relative error covariance analysis techniques and application

A technique for computing the error covariance of the difference between two estimators derived from different (possibly overlapping) data arcs is presented. The relative error covariance is useful for predicting the achievable consistency between Kalman-Bucy filtered estimates generated from two (not necessarily disjoint) data sets. The relative error covariance analysis technique is then applied to a Venus Orbiter simulation.

Wolff, Peter, J.↗

Spillover stabilization of large space structures

Active control of large flexible space structures is typically implemented to control only a few known elastic modes. This paper considers the stabilization of the neglected dynamics of the higher modes of vibration. An attempt is made to design modal controllers with improved spillover stability properties. Two formulations for designing the observer to improve spillover stability with minimum performance loss are proposed. One optimizes the noise statistics used in the design of the Kalman-Bucy Filter (KBF), while the other directly optimizes the the gain matrix of the KBF.

Czajkowski, Eva A.↗

Airborne gravimetry, altimetry, and GPS navigation errors

Proper interpretation of airborne gravimetry and altimetry requires good knowledge of aircraft trajectory. Recent advances in precise navigation with differential GPS have made it possible to measure gravity from the air with accuracies of a few milligals, and to obtain altimeter profiles of terrain or sea surface correct to one decimeter. These developments are opening otherwise inaccessible regions to detailed geophysical mapping. Navigation with GPS presents some problems that grow worse with increasing distance from a fixed receiver: the effect of errors in tropospheric refraction correction, GPS ephemerides, and the coordinates of the fixed receivers. Ionospheric refraction and orbit error complicate ambiguity resolution. Optimal navigation should treat all error sources as unknowns, together with the instantaneous vehicle position. To do so, fast and reliable numerical techniques are needed: efficient and stable Kalman filter-smoother algorithms, together with data compression and, sometimes, the use of simplified dynamics.

Colombo, Oscar L.↗