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The problem of estimating the state of a linear dynamic system driven by additive gaussian noise with unknown time varying statistics is considered. Estimates of the state of the system are obtained which are based on all past observations of the system. These observations are linear functions of the state contaminated by additive white gaussian noise with unknown time varying statistics. The case...
The solution of the Riccati equation corresponding to the Kalman filter, with a single perfect measurement and possibly one or more noisy measurements, requires the numerical integration of a nonlinear matrix differential equation whose dimension is one less than that of the system state vector. A similar requirement exists for the linear regulator problem when one of the controls has no penalty and...
This paper describes a specific postflight data analysis (PFDA) technique, which is termed adaptive, iterated, extended Kalman filtering (AIEKF), and illustrates the application of this PFDA tool to the estimation of aerodynamic coefficients (Cx, CN, and Cm) for a single-axis model of a thrust-vector-controlled missile.
The problem of making the transfer function between disturbances and controlled outputs identically zero by using state feed-back, feedforward control and dynamic compensation in a linear time invariant system is treated and a constructive solvability condition is presented.
The problem of the minimization of a functional of several parameters is treated. It is supposed that the gradient of the functional is known but the stochastic approximation method cannot be applied since its convergence is not guaranteed due to the form of the functional. A mixed random search-stochastic approximation method insuring this convergence is developed. Several applications in the field...
We investigate a stochastic penalty algorithm, which can be used to find a constrained optimum point for a concave or convex objective function subject to a nonlinear constraint which forms a connected region, even when we do not have the objective function available, but only have a noisy estimate of the objective function. When the constraint consists of one linear equation, we prove convergence...
A prefiltering version of the Kalman filter is derived for both discrete and continuous measurements. The derivation consists of determining a single discrete measurement that is equivalent to either a time segment of continuous measurements or a set of discrete measurements. This prefiltering version of the Kalman filter easily handles numerical problems associated with rapid transients and ill-conditioned...
Data filtering with presmoothed measurements is a useful technique for data compression in high data rate, noisy measurement systems. A sequential filtering algorithm is derived for processing integrated measurements, and the algorithm is applied to data filtering with discrete presmoothed measurements. Prefilter trade studies with a two dimension system show that the algorithm may provide a large...
This paper describes a CAI (computer-aided instruction) system which is based on algorithms for problem generation and solution. A heuristic monitor has been developed which tailors the path taken by each student through the course concepts in accordance with his previous performance. This monitor will be described as well as general techniques for problem generation and solution monitoring.
A method is presented for estimating the parameters of a fixed order autoregressive moving average model, based on maximization of an appropriate likelihood function. The resulting static optimization is accomplished with a modified Newton numerical algorithm. Under suitable initial conditions for the model, the gradient and hessian matrices of each iteration can be compted analytically. Because of...
The Dyer-McReynolds square root information filter (SRIF) is rederived, using recursive least squares arguments. The result is applied to a system composed partly of biases. The filter "sensitivity" matrix, "computed" covariance, and "consider" covariance for this augmented system are reviewed. A new computationally attractive representation for the smoothed estimates,...
A new algorithm is proposed for estimating the state of a nonlinear stochastic system when only noisy observations of the state are available. The state estimation problem is formulated as a modaltrajectory maximum-likelihood estimation problem. The resulting minimization problem is analogous to the nonlinear tracking problem in optimal control theory. By viewing the system as an interconnection of...
This paper describes some design considerations of a navigation filter for an unmanned aircraft. Emphasis is on a simple, but accurate approach to navigation. Design considerations are discussed for the implementation of a fixed gain extended Kalman filter. Representative sensors including true airspeed, doppler, and LORAN are described, and their integration into a modular navigation system is explained.
An adaptive probability state variable (PSV) parameter search algorithm Possessing long-term memory has been formulated to cope with systems that must avoid high performance-penalty operating regions. The information gained from all previous experiments is efficiently encoded in multivariate probability distribution functions (pdf's). This long-term memory capability enables the PSV algorithm effectively...
This paper describes different types of patterning which exist in such diverse types of data as speech, text, and pictorial scenes. Several programs which process such data are discussed in terms of contextual, syntactic, semantic, and problem-domain dependent factors. Each of these factors constitutes a potential level of computer processing. By introducing different processing levels each having...
When a computer system is handling its workload in a multiprogramming environment, it has to control a concurrent execution of a number of user programs or processes. These processes make use of various hardware and software resources of the system, some of which are capable of autonomous, parallel operation. The computer system sources while allowing a systematic execution of user jobs via its Operating...
A method is presented for generating the optimal control of a linear system from measurements of the system input and output. The systems considered are n-th order, time invariant or time varying forced linear systems which are restricted to be bounded and uniformly completely state reconstructible. The control is generated from an estimate of the state vector which is obtained from an observer. The...
This paper discusses a well known change of co-ordinates for multiple output systems from a different viewpoint, and a new, simplified, low order observer design. The discussion of the transformation given here exhibits more of the system structure than previous presentations. The observer design procedure does not require explicitly performing a change of basis on the system, and includes the construction...
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