Showing papers on "Observer (quantum physics) published in 1970"

Optimal minimal-order observer-estimators for discrete linear time-varying systems

Abstract: This paper generalizes and unifies the concepts developed by Kalman and Luenberger pertaining to the design of discrete linear systems which estimate the state of a linear plant on the basis of both noise-free and noisy measurements of the output variables. Classes of minimal-order optimum "observer-estimators" are obtained which yield the conditional mean estimate of the state of the dynamical system. One explicit minimal-order optimal observer-estimator is constructed which generates one version of the conditional mean state estimate.

The synthesis of regulator logic using state-variable concepts

Abstract: This is a tutorial paper. It was written for technically knowledgeable people who are not specialists in automatic control. It might also be of some use in university courses in automatic control. Linear feedback of the state variables for stationary linear plants permits choice of the gains to place poles (eigenvalues) of the controlled system in desired locations. Continuous estimates of the state variables can often be made from one or more measurements of the output using a filter of the same (or lower) order as the plant called "an observer": the poles of the observer can be placed arbitrarily through choice of the observer gains. Combining an observer with state-variable feedback yields a "compensator" design; the poles of the controlled system are the poles of the observer plus the poles of plant with state-variable feedback, which greatly simplifies the design problem.

Specific optimal control of the linear regulator using a dynamical controller based on the minimal-order Luenberger observer†

Abstract: The problem is considered of designing the optimal, fixed configuration, dynamical feedback controller of order (n—m) required to control an nth-order linear system with output of order m(m

Target Detection through Visual Recognition: A Quantitative Model

Abstract: : The report presents a model for describing analytically the capabilities and limitations of a human observer in the task of looking for and finding known or expected fixed objects. The description takes the form of six algebraic equations which together enable the user to estimate recognition probabilities as a function of the many parameters required to describe a specific situation. The model is tailored to the case of an airborne observer looking at terrain with or without optical aids or electro-optical sensors, but with prior knowledge of the approximate appearance of an object.

Relationship Between State-space And Input-outputModels Via Observer Markov Parameters

Abstract: This paper describes the relationship between two types of commonly used models in control and identification theory: state-space and input-output models. The relationship between the two model structures can be explained in terms of a newly formulated set of parameters called the observer Markov parameters. This is different from the usual connection between the two model structures via well-known canonical realizations. The newly defined observer Markov parameters generalize the standard system Markov parameters by incorporating information of an associated observer. In the deterministic case, the observer Markov parameters subsume a state-space model and a deadbeat observer gain In the stochastic case, the observer Markov parameters contain information of an optimal observer such as a Kalman filter. The observer Markov parameters can be identified directly from experimental input-output data. Making use of the new connection, one can extract from the identified observer Markov parameters not only a state-space model of the system, but also an associated observer gain for use in modern state-space based feedback controller design.

On the optimal control of linear systems with incomplete information

Abstract: : The control of linear systems with incomplete information is considered where the unknown disturbances and/or random parameters are assumed to satisfy some statistical laws. The observer theory for linear systems is developed which generalizes the concepts due to Kalman and Luenberger pertaining to the design of linear systems which estimate the state of a linear plant on the basis of both noise-free and noisy measurements of the output variables. The separation theorem for linear system is then extended for such observers- estimators. The problem of controlling a linear system with unknown gain is then considered. An open-loop-feedback-optimal control algorithm is developed which seems to be computationally feasible. Existence of such suboptimal control scheme is proved under the assumption that the uncertainties in the unknown gail will not grow in time. Convergence of such suboptimal control system to the truly optimal control system is considered. A computer program is developed to study the control of a variety of third order systems with known poles but unknown zeroes. The experimental results serve to provide more insights into the structure and behavior of the open-loop-feedback-optimal control systems.

Transfer-function matrix approach to observer design

Abstract: The properties of the Luenberger observer are developed in a straightforward manner from the transfer function-matrix viewpoint, and an algorithm is presented for the generation of a class of least-order observer designs. These developments, with the observation that a dual of the observer can be used to supply additional plant inputs, should lead to new techniques for the design of dynamic compensators for linear multivariable systems.

Observation and control of linear systems with constant disturbances

Abstract: The problem of regulation in the presence of a fixed but unknown disturbance is considered. The control law is designed as if the disturbance were known, and an estimate given by an observer is used in the control law. A system results having as many integrators as outputs.

On the use of observers in finite-time optimal regulator problems†

Abstract: When a compatible dynamical observer is employod to construct the estimates of the inaccessible states of the system, an increase in the value of the performance index of a finite-time optimal regulator is in general encountered. An expression for this increase in the value is derived. The conditions for zero increase in the cost are discussed.

A study of the tachistoscope

Abstract: Describes the tachistoscope, which is a device for presenting a visual field to an observer for a carefully controlled time interval. Goes on to show the differences between the newer and the older types and its use as an advertising research tool, showing is a successful aid for this purpose. Reports an experiment conducted on the tachistoscope, gives an analysis and summarises the results. Concludes, if results from testing can be shown to be valid, then useful research could be carried out to establish results.

Correlation of the Frequency Spectrum of a Pulmonary Nodule with Observer Detection Rate

Abstract: Intercostal nodules were placed on chest films and a study made of the relationship between the frequency spectrum presented by an image and an observer's ability to detect it. Both the cumulative frequency spectrum curve and the correct detection rate approach 100% at about 2.2 cycles/cm. Below 100%, detection rate lags significantly.

A stochastic model for the quantum theory in vision

Abstract: Light quanta arrive at times τ 1 , τ 2 ,… on the retina of one eyes of an observer, each quantum giving rise to a unit response, lasting its lifetime. The characteristic functional of the cumulative response at any time t is obtained when the light quanta arrive according to any general point process, their lifetimes being independently, identically, and arbitrarily distributed. Various quantities of interest in the sensory phenomenon are discussed.

Minimum variance estimates of signal derivatives - A problem in instrument landing systems

Abstract: Kalman filter application as observer of observable signals derivatives, using gain matrix to minimize variance estimate for instrument landing systems

A Computer Program for Calculation of Scott's Coefficient of Observer Reliability.

Abstract: EDRS Price MF-$0.25 HC-$0.60 *Classroom Observation Techniques, *Computer Programs, Educational Research, *Reliability, *Research Methodology, *Statistical Analysis FORTRAN, Inter rater Reliability, Observer Reliability Scott's coefficient is an improved method for estimating observer reliability using any system which assigns events to mutually exclusive categories. The formula is the ratio of the actual difference between obtained and chance agreement to the maximum difference between obtained and chance agreement. A FORTRAN program for calculating this reliability coefficient is presented. The program can be used with from 2 to 20 observers and can include any number of observations as long as the product of the observations times the observers does not exceed 200. The observation system cannot exceed 30 categories. There are four outputs of the program including the average reliability coefficient of all possible pairs of observers, the average difference between all possible pairs cf observers for each category, the percentage of each observer's total assignments found in each category, and each observer's average coefficient cf reliability with all other observers. The data deck arrangement and program listing are included. (PR) THE RESEARCH AND DEVELOPMENT CENTER FOR TEACHER EDUCATION THE UNIVERSITY OF TEXAS Ki k"4"11 AUSTIN / AUSTIN PUBLIC 0=.1 SCHOOLS / TT::XAS EDUEll "I CATION AGENCY C:) U.S. DEPARTMENT OF HEALTH, EDUCATION Pe\ & WELFARE OFFICE OF EDUCATION THIS DOCUMENT HAS BEEN REPRODUCED EXACTLY AS RECEIVED FROM THE PERSON OR tin ORGANIZATION ORIGINATING IT. POINTS OF VIEW OR OPINIONS STATED DO NOT NECES.4 SARILY REPRESENT OFFICIAL OFFICE OF EDUCATION POSITION OR POLICY. A COMPUTER GROGRAM FOR CALCULATION OF SCOTT'S COEFFICIENT OF OBSERVER RELIABILITY

Application of the Kalman Filter to Orbit Determination.

Abstract: : The paper presents such a method by applying Kalman Filter theory to determine the position and velocity of near-earth satellites using data from a fixed observer on the Earth. The vehicle equations of motion are linearized in a Taylor Series expansion. The nominal states, position and velocity, are determined by integrating the nonlinear equations of motion, and the linear filter theory is used to estimate the errors in these states. The linear estimated errors are added to the nominal states to obtain an updated trajectory which is used as the starting point on a new nominal for the next integration. Actual tracking data from four different satellites are used in the study. Convergence of the error estimates to values less than 0.1 per cent of the best estimates of position and velocity is obtained within 50-250 seconds from the time of the initial radar contact. The program is capable of integrating for over 80 seconds with no tendency to diverge. The rate of convergence is related to the initial guess of the error covariance matrix, along with the measurement accuracy of the tracking stations. Results are presented in both tabular and graphical form. (Author)

The application of a theoretical learning model to a remote handling control system.

Abstract: : The report introduces the concept of adaptive aiding as a means of improving performance in remote handling, and describes the development, realization and experimental evaluation of a system based on this concept. The system incorporates an automaton that is able to supplement the operator's control of a powered manipulator arm as well as act as a parallel controller. The operator positions the manipulator in three dimensions by means of joystick control; a foot-pedal opens and closes the manipulator claw. The behavior of the automaton is established through a process of learning -- observing the human operator's control actions relative to the environment and the manipulator output, and developing a decisionmaking policy. Initially, the manipulator is totally controlled by the operator, while the automaton acts as a passive observer. As operation continues, behavior patterns are acquired by the automaton, and gradually it is transformed from a passive observer to an active controller. (Author)

Development of violation sampling and recording techniques

Abstract: THE PURPOSE WAS TO DEVELOP AND "DE-BUG" PREFERRED COST-EFFECTIVE SYSTEMS TO SAMPLE AND RECORD TRAFFIC VIOLATIONS. THIS REPORT PROVIDES THE DETAILED STUDIES CONDUCTED TO EVALUATE CANDIDATE SYSTEMS FOR MEASURING TRAFFIC VIOLATIONS, AND IT PRESENTS THE RESULTS OF FIELD TESTS OF THOSE SYSTEMS WHICH WERE SHOWN TO BE THE MOST PROMISING FOR GENERAL APPLICATION. THE SYSTEMS DEVELOPED AND TESTED INCLUDE A ROAD-TUBE SENSING SYSTEM, A TIME-LAPSE PHOTOGRAPHY SYSTEM, HUMAN OBSERVER SPOT STUDIES, AND THE CAR-BOURNE OBSERVER STUDIES. /HSL/

Toward a General Theory of Measurement. I

Abstract: A self‐consistent measurement theory is set forth in this paper, which can be applied to the problem of measurement in field theory. Following the formulation of Birkhoff and von Neumann, we construct a system of axioms sufficient to ensure that it is possible to find an implicit mechanism within each theory for the experimental procedure corresponding to each observable proposition of that theory. It is shown that any theory of a type similar to quantum mechanics cannot consistently describe a closed system from the point of view of a single observer.