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One of the most important parameters in air-air guided missile performance is the navigation ratio. A technique for on-line estimation and control of the navigation ratio for a typical tactical, air-air guided missile is described.
Digital fly-by-wire flight control systems are currently of interest because simple mechanical linkages are no longer able to cope with the many control problems associated with high performance aircraft. In view of this, a digital adaptive flight control algorithm has been developed by combining a weighted least squares estimator with optimal linear regulator control logic designed to minimize a...
The paper is an outline of a talk that will survey some algorithms that have recently been developed for linear estimation in dynamical systems with time-invariant parameters. The algorithms have potential numerical advantages and in particular require less effort than the Kalman filter. Special cases of the algorithms are closely related to certain early (1947) work in astrophysics by So Chandrasekhar...
This paper presents a functional analysis solution to the discrete optimal control problem with quadratic cost functional, dealing with the case of unconstrained control and fixed endpoints.
This paper reports a reasonably complete theory of necessary and sufficient conditions for a control to be superior with respect to a non-scalar-valued performance criterion. The latter maps into a finite-dimensional integrally closed directed partially ordered linear space. The applicability of the theory to the analysis of dynamic vector estimation problems and to a class of uncertain optimal control...
An optimal control in a stochastic system is often one which minimizes the mean value of a specified performance index. Exclusive concern with this single parameter of dynamic response may mask anomalous behavior which occurs with small probability. Before utilizing an optimal controller further study of its properties is warranted. This paper provides an algorithm for finding an approximation to...
In this paper, a computer control technique for controlling a class of largely uncertain multivariable plants using model tracking method is presented. The approach uses a "Two-level" controller, with a feedforward controller on its first-level, and a conditional feedback controller on its second-level. The design procedure presented employs the deterministic type Liapunov signal synthesis...
This paper describes the development and operation of a vehicle scheduling algorithm which has applications to the NASA problem of assigning payloads to space delivery vehicles. The algorithm is based on a discrete, integer-valued, non-serial, dynamic programming solution to the classical problem of developing resource utilization plans with limited resources. The algorithm places special emphasis...
The problem of control of a stochastic system with control dependent noise is investigated. Both the system driving noise and system measurement noise are assumed to have control dependent terms. The approximation of neglecting higher order terms in the control is introduced in the derivation of the a posteriori conditional covariance matrices of the system state. These approximate conditional covariance...
A brief discussion of two types of tapped delay-line channel simulators which were built is presented: simulators which model the behavior of the channel, and simulators which reproduce the behavior of the channel. In the latter case, channel measurements were made to provide the control voltages for the reproduction. Some VHF simulation results are given. Adaptive functions of the receiver requiring...
A combined primal-dual and penalty method is given for solving the nonlinear programming problem. The algorithm generalizes the "method of multipliers" and is applicable to problems with both equality and inequality constraints. The algorithm is defined for a broad class of "penalized Lagrangians," and is shown to be globally convergent when applied to the convex programming problem...
This paper surveys some of the unifying approaches used to derive formulae for updating the inverse Hessian approximations in quasi-Newton algorithms and presents a new approach of this kind based on geometric considerations. The paper discusses the intuitive motivations for these approaches and their potential in providing explanations for observed behavior of such algorithms.
A transportation control system maintains the flow of traffic according to a schedule by implementing various policies (e.g. procedures, rules, priorities, etc.). In a conventional control system the schedule is fixed and the policies are deterministic. An adaptive control system, on the other hand, has an internal mechanism for altering its policies which, in turn, adjust the schedule in response...
This paper describes an eigenvector decomposition of an m ? n rectangular matrix, P0. Matrix P0 is approximated as a series of matrices each one of which can be expressed as the outer product of two vectors. These vectors are of dimensions m ? 1 and n ? 1; thus, each term in the approximation to P0 requires m + n storage locations. If P0 is approximated by a series of l matrices, then l(m + n) storage...
We consider an information source which is an i.i.d. binary sequence governed by unknown probability measures. The information sequence is transferred through a memoryless binary channel with unknown cross-over probabilities. The channel model also represents those cases in which an input quantizer is always used, so that the incoming information-bearing observations are threshold crossings of the...
Let the given covariance stationary process y(.) obey a linear stochastic difference equation made up of y(k) and its n1 lagged values, the observable input u(k) and Its n3 lagged values, the unobservable input w(k) derived from a zero mean white noise sequence, and n2 deterministic sinusoidal trend terms ?j(k), J=1,...,n2, the coefficients of all the terms being unknown. Our intention is to identify...
The subject of this paper is the application of stochastic control theory to resource allocation under uncertainty. In these problems it is assumed that the results of a given allocation of resources are not known with certainty, but that a limited number of experiments can be performed to reduce the uncertainty. The problem is to develop a policy for performing experiments and allocating resources...
Two new algorithms are proposed for identifying the noise means required before Kalman Filtering. These algorithms use the results of Part I of this paper, i.e., the identified noise intensities (or the optimal predictor gain if the noise intensities cannot be identified). To be Compatible with the algorithms of Part I, the algorithms described here are also nonrecursive. They are based on the maximum-likelihood...
This paper presents modified formulations of the generalized least squares estimation algorithm for system parameter identification. Two sets of results are derived: First the existing algorithm is reformulated by eliminating the intermediate filtering procedures and introducing the system's input-output correlation matrices. Then it is shown that the new algorithm can be conveniently simplified to...
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