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At least 595 records · Page 33

Application of the Two-Step Filter to Process Ranging Measurements for Relative Navigation in an Elliptical Orbit

This estimator breaks a nonlinear estimation problem into a set of over determined 'first step' states which are linear in the observations and 'second step' states which are ultimately the states of interest. Linear estimation methods are applied to filter the observations and produce the optimal first step state estimate. The 'second step' states are obtained through iterative nonlinear parameter estimation considering the first step states as observations. It has been shown that this process exactly minimizes the least squares cost function for static problems and provides a better solution than the iterated extended Kalman filter (EKF) for dynamic problems. The two step filter is applied in this paper to process range and range rate measurements between the two spacecraft. Details of the application of the two step estimator to this problem will be given, highlighting the use of a test for ill-conditioned covariance estimates that can result from the first order covariance propagation. A comparison will be made between the performance of the two step filter and the IEKF.

Garrison, James L.↗

Data acquisition and path selection decision making for an autonomous roving vehicle

Problems related to the guidance of an autonomous rover for unmanned planetary exploration were investigated. Topics included in these studies were: simulation on an interactive graphics computer system of the Rapid Estimation Technique for detection of discrete obstacles; incorporation of a simultaneous Bayesian estimate of states and inputs in the Rapid Estimation Scheme; development of methods for estimating actual laser rangefinder errors and their application to date provided by Jet Propulsion Laboratory; and modification of a path selection system simulation computer code for evaluation of a hazard detection system based on laser rangefinder data.

Frederick, D. K.↗

A Quantum Algorithm to Simulate Open Quantum Systems

Given the advent of quantum algorithms for a wide array of problems in linear algebra and machine learning, it is important to develop general methods for the simulation of arbitrary (ie non-unitary) operators on quantum hardware. In this talk, we present a novel quantum algorithm based on the quantum singular value transformation (QSVT) to apply an arbitrary operator K to some input state and subsequently estimate the expectation value of some observable. Our construction then immediately yields a route to estimating observables of states undergoing open quantum dynamics, whose effect is captured by a set of non-unitary Kraus operators. Our algorithm succeeds deterministically given the Sz-Nagy dilation, and we provide details on the algorithm's query and gate complexity, numerical verification, and comparisons with prior methods.

Quantum computing↗

Estimates of software size from state machine designs

The length, or size (in number of Source Lines of Code) of programs represented as state machines, it is demonstrated, can be reliably estimated in terms of the number of internal state machine variables.

Britcher, R. N.↗

Experimental studies in system identification of helicopter rotor dynamics

Recent experiments investigating the system identification of helicopter rotor dynamics are described. The identification makes use of a two-pass procedure that estimates the rotor dynamic states prior to estimation of the dynamic equation parameters. Estimation of the rotor states is made possible through use of the predictive information contained in blade-mounted accelerometers combined with a specialized processing scheme utilizing these signals. Descriptions of the experimental hardware and the system identification technique are given, as well as implementation issues for using the procedure on other similarly instrumented rotor blades. Finally, comparisons with other identification techniques using the same data are presented. It is demonstrated that the approach is an attractive one for measurement of a helicopter rotor's dynamic behavior.

Mckillip, Robert, Jr.↗

Detection and estimation theory

Equalization of dispersive channels using decision feedback, and state variable estimation of sonar or seismic data in presence of pure delay

COMMUNICATION THEORY↗

An Automated Technique for Estimating Daily Precipitation over the State of Virginia

Digital IR and visible imagery obtained from a geostationary satellite located over the equator at 75 deg west latitude were provided by NASA and used to obtain a linear relationship between cloud top temperature and hourly precipitation. Two computer programs written in FORTRAN were used. The first program computes the satellite estimate field from the hourly digital IR imagery. The second program computes the final estimate for the entire state area by comparing five preliminary estimates of 24 hour precipitation with control raingage readings and determining which of the five methods gives the best estimate for the day. The final estimate is then produced by incorporating control gage readings into the winning method. In presenting reliable precipitation estimates for every cell in Virginia in near real time on a daily on going basis, the techniques require on the order of 125 to 150 daily gage readings by dependable, highly motivated observers distributed as uniformly as feasible across the state.

Follansbee, W. A.↗

State and model error estimation for distributed parameter systems

In-flight estimation of large structure model errors in order to detect inevitable deficiencies in large structure controller/estimator models is discussed. Such an estimation process is particularly applicable in the area of shape control system design required to maintain a prescribed static structural shape and, in addition, suppress dynamic disturbances due to the vehicle vibrational modes. The paper outlines a solution to the problem of static shape estimation where the vehicle shape must be reconstructed from a set of measurements discretely located throughout the structure. The estimation process is based on the principle of least-squares that inherently contains the definition and explicit computation of model error estimates that are optimal in some sense. Consequently, a solution is provided for the problem of estimation of static model errors (e.g., external loads). A generalized formulation applicable to distributed parameters systems is first worked out and then applied to a one-dimensional beam-like structural configuration.

Rodriguez, G.↗

Design of a robust multivariable proportional plus integral controller via spectral assignment

A new design procedure for a class of multivariable integral plus proportional servo control systems is presented. The procedure utilizes a null space formulation of the eigensystem assignment problem assuming complete state feedback. Reduced order observers are used to estimate unavailable states. The resulting system realizes arbitrary closed-loop eigenvalues, approximates specified modal behavior and achieves low eigensystem sensitivity with respect to plant parameter variations. A tutorial example to illustrate the design procedure is included.

Mielke, R. R.↗

State and model error estimation for elliptic systems: Applications to large antenna static shape determination

This paper outlines the application of various estimation approaches to the problem of static shape determination for large antenna systems. The problem consists of estimating the shape of an antenna surface from measurements of its static deflection. The estimation schemes are based on any one of the modeling options of a single PDE for early insight and understanding, coarse-resolution multiple-PDE models for parametric studies and fine-resolution piecewise-continuum models for detailed design. For any one of these three models, estimator design can be developed using an infinite-dimensional approach, where the necessary finite-element truncation and approximation is conducted after the analytical design has taken place, or it can be based on a finite-dimensional approach, where the model is truncated before the estimation problem is formulated. One of the main objectives of the paper is to develop both approaches while simultaneously investigating their differences and similarities. Simulation results of an application of the finite-dimensional approach to a large parabolic reflector are presented.

Rodriguez, G.↗

An efficient method for estimating neighboring steady-state numerical solutions to the Euler equations

The paper concentrates on a linear approximation method for predicting the changes occurring in steady-state numerical solutions of the Euler equations as a consequence of small changes in the independent variables which control the problem. The importance of proper boundary-condition treatment and other issues concerning the problem are covered along with the importance of proper algorithm selection for a fully supersonic inviscid flow. The method is applied to a subsonic nozzle involving variation of the pressure on the outflow boundary and to a supersonic inlet involving variation of the inflow Mach number. In the subsonic test case, the comparisons between the predicted and conventional numerical solutions are shown to be good, while in the supersonic test case, the agreement between the approximation method and conventional numerical solution starts out well but rapidly degenerates at some point in the flowfield as the perturbation of the boundary conditions is increased.

Taylor, Arthur C., III↗

Vehicle-Level Reasoning Systems: Integrating System-Wide Data to Estimate the Instantaneous Health State

At the aircraft level, a Vehicle-Level Reasoning System (VLRS) can be developed to provide aircraft with at least two significant capabilities: improvement of aircraft safety due to enhanced monitoring and reasoning about the aircrafts health state, and also potential cost savings by enabling Condition Based Maintenance (CBM). Along with the benefits of CBM, an important challenge facing aviation safety today is safeguarding against system and component failures and malfunctions. Faults can arise in one or more aircraft subsystem their effects in one system may propagate to other subsystems, and faults may interact.

system-wide data↗

Representation of Probability Density Functions from Orbit Determination using the Particle Filter

Statistical orbit determination enables us to obtain estimates of the state and the statistical information of its region of uncertainty. In order to obtain an accurate representation of the probability density function (PDF) that incorporates higher order statistical information, we propose the use of nonlinear estimation methods such as the Particle Filter. The Particle Filter (PF) is capable of providing a PDF representation of the state estimates whose accuracy is dependent on the number of particles or samples used. For this method to be applicable to real case scenarios, we need a way of accurately representing the PDF in a compressed manner with little information loss. Hence we propose using the Independent Component Analysis (ICA) as a non-Gaussian dimensional reduction method that is capable of maintaining higher order statistical information obtained using the PF. Methods such as the Principal Component Analysis (PCA) are based on utilizing up to second order statistics, hence will not suffice in maintaining maximum information content. Both the PCA and the ICA are applied to two scenarios that involve a highly eccentric orbit with a lower apriori uncertainty covariance and a less eccentric orbit with a higher a priori uncertainty covariance, to illustrate the capability of the ICA in relation to the PCA.

Mashiku, Alinda K.↗

Preliminary Design of the Guidance, Navigation, and Control System of the Altair Lunar Lander

Guidance, Navigation, and Control (GN&C) is the measurement and control of spacecraft position, velocity, and attitude in support of mission objectives. This paper provides an overview of a preliminary design of the GN&C system of the Lunar Lander Altair. Key functions performed by the GN&C system in various mission phases will first be described. A set of placeholder GN&C sensors that is needed to support these functions is next described. To meet Crew safety requirements, there must be high degrees of redundancy in the selected sensor configuration. Two sets of thrusters, one on the Ascent Module (AM) and the other on the Descent Module (DM), will be used by the GN&C system. The DM thrusters will be used, among other purposes, to perform course correction burns during the Trans-lunar Coast. The AM thrusters will be used, among other purposes, to perform precise angular and translational controls of the ascent module in order to dock the ascent module with Orion. Navigation is the process of measurement and control of the spacecraft's "state" (both the position and velocity vectors of the spacecraft). Tracking data from the Earth-Based Ground System (tracking antennas) as well as data from onboard optical sensors will be used to estimate the vehicle state. A driving navigation requirement is to land Altair on the Moon with a landing accuracy that is better than 1 km (radial 95%). Preliminary performance of the Altair GN&C design, relative to this and other navigation requirements, will be given. Guidance is the onboard process that uses the estimated state vector, crew inputs, and pre-computed reference trajectories to guide both the rotational and the translational motions of the spacecraft during powered flight phases. Design objectives of reference trajectories for various mission phases vary. For example, the reference trajectory for the descent "approach" phase (the last 3-4 minutes before touchdown) will sacrifice fuel utilization efficiency in order to provide landing site visibility for both the crew and the terrain hazard detection sensor system. One output of Guidance is the steering angle commands sent to the 2 degree-of-freedom (dof) gimbal actuation system of the descent engine. The engine gimbal actuation system is controlled by a Thrust Vector Control algorithm that is designed taking into account the large quantities of sloshing liquids in tanks mounted on Altair. In this early design phase of Altair, the GN&C system is described only briefly in this paper and the emphasis is on the GN&C architecture (that is still evolving). Multiple companion papers will provide details that are related to navigation, optical navigation, guidance, fuel sloshing, rendezvous and docking, machine-pilot interactions, and others. The similarities and differences of GN&C designs for Lunar and Mars landers are briefly compared.

Lee, Allan Y.↗

Supervision of dynamic systems: Monitoring, decision-making and control

Effects of task variables on the performance of the human supervisor by means of modelling techniques are discussed. The task variables considered are: The dynamics of the system, the task to be performed, the environmental disturbances and the observation noise. A relationship between task variables and parameters of a supervisory model is assumed. The model consists of three parts: (1) The observer part is thought to be a full order optimal observer, (2) the decision-making part is stated as a set of decision rules, and (3) the controller part is given by a control law. The observer part generates, on the basis of the system output and the control actions, an estimate of the state of the system and its associated variance. The outputs of the observer part are then used by the decision-making part to determine the instants in time of the observation actions on the one hand and the controls actions on the other. The controller part makes use of the estimated state to derive the amplitude(s) of the control action(s).

White, T. N.↗

Distributed Damage Estimation for Prognostics based on Structural Model Decomposition

Model-based prognostics approaches capture system knowledge in the form of physics-based models of components, and how they fail. These methods consist of a damage estimation phase, in which the health state of a component is estimated, and a prediction phase, in which the health state is projected forward in time to determine end of life. However, the damage estimation problem is often multi-dimensional and computationally intensive. We propose a model decomposition approach adapted from the diagnosis community, called possible conflicts, in order to both improve the computational efficiency of damage estimation, and formulate a damage estimation approach that is inherently distributed. Local state estimates are combined into a global state estimate from which prediction is performed. Using a centrifugal pump as a case study, we perform a number of simulation-based experiments to demonstrate the approach.

Daigle, Matthew↗