Unmodeled Features Research Articles

PID controller with feed forward estimation used for fault tolerant control of hydraulic system

The paper stresses on the designing and implementation of a nonlinear offline feed forward controller in association with a PID controller as a fault tolerant control measure for a closed loop hydraulic system. An off-line nonlinear feed forward control with proportional pressure relief valve (PRV) loading on the loading pump has been developed using the subsystem models without taking into considerations the oil compressibility, valve dynamics and leakages associated with various components of the hydraulic circuit. A PID feedback has been utilized in real-time to deal with the unmodeled features and the modelling approximations. The characteristics of the speed response are significantly influenced by the disturbances related to external torque, change in the input magnitude as well as system parameters like inertia load and supply pressure. The real-time control showed that the experimental and predicted closed–loop control performances justify each other quite well. Hence, the PID gains were estimated quite effectively with the help of the developed simulation tool here. The control model produced good agreement between the demanded and real-time speed response for various loading conditions such as step load, sinusoidal load, variable load, triangular load etc.

Adaptive robust control and admittance control for contact-driven robotic surface conditioning

Abstract This work presents a hybrid position/force control of robots for surface contact conditioning tasks such as polishing, profiling, deburring, etc. The robot force control is designed using sliding mode ideas to benefit from robustness. On the one hand, a set of equality constraints are defined to attain the desired tool pressure on the surface, as well as to keep the tool orientation perpendicular to the surface. On the other hand, inequality constraints are defined to adapt the tool position to unmodeled features present in the surface, e.g., a protruding window frame. Conventional and non-conventional sliding mode controls are used to fulfill the equality and inequality constraints, respectively. Furthermore, in order to deal with sudden changes of the material stiffness, which are forwarded to the robot tool and can produce instability and bad performance, adaptive switching gain laws are considered not only for the conventional sliding mode control but also for the non-conventional sliding mode control. A lower priority tracking controller is also defined to follow the desired reference trajectory on the target surface. Moreover, the classical admittance control typically used in force control tasks is adapted for the proposed surface contact application in order to experimentally compare the performance of both control approaches. The effectiveness of the proposed method is substantiated by experimental results using a redundant 7R manipulator, whereas its advantages over the classical admittance control approach are experimentally shown.

Rapid S-Curve Update Using Ensemble Variance Analysis With Model Validation

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 185630, “Rapid S-Curve Update Using Ensemble Variance Analysis With Model Validation,” by Jincong He, Shusei Tanaka, Xian-Huan Wen, and Jairam Kamath, Chevron, prepared for the 2017 SPE Western Regional Meeting, Bakersfield, California, USA, 23–27 April. The paper has not been peer reviewed. In the complete paper, the authors propose a novel method to rapidly update the prediction S-curves given early production data without performing additional simulations or model updates after the data come in. The approach has been successfully applied in a Brugge waterflood benchmark study, in which the first 2 years of production data [rate and bottomhole pressure (BHP)] were used to update the S-curve of the estimated ultimate recovery. To the authors’ knowledge, the proposed work flow, including the model validation and the denoising techniques, is novel. The proposed work flow is also general enough to be used in other model-based data-interpretation applications. Introduction As surveillance data are obtained from the field, the S-curves of the key metrics need to be updated accordingly. This is normally accomplished by a two-step approach. First, the data are assimilated through history matching to calibrate the model parameter uncertainties to obtain their posterior distributions. Then, a probabilistic forecast is performed on the basis of the posterior distributions of the parameters to update the S-curve of the key metrics. However, obtaining an S-curve update with the traditional approach can take weeks or months after the data come in. There is a need for rapid interpretation of the incoming data and update of the S-curve without going through a full-blown history-matching and probabilistic-forecast process. Recently, the approach called direct forecast (also called data-space inversion) has been a focus of attention. In direct forecast, the statistical relationship between the measurement data and the business objective is established on the basis of simulation-model responses before the data acquisition. This direct relationship can then be used to rapidly update the prediction of the objective once the data become available. A process called canonical functional component analysis is proposed to map the data and forecast variables into a low-dimensional space; multilinear regression was implemented in the reduced space to establish the data/objective relationship. The authors explore the use of a simpler and more-intuitive method called ensemble variance analysis (EVA) for rapid update of the S-curve. The idea of EVA is to explore covariance between data and objectives, then use an analytical formula to calculate the posterior S-curve. In the complete paper, the authors adapt the formulation for rapid S-curve update after data come in. While the direct forecast has attracted attention, less attention has been paid to validating the consistency between observed data and the simulation model after data come in. Blindly applying the direct-forecasting formula without identifying unmodeled features can lead to an incorrect posterior S-curve and misinformed decisions. The authors propose a procedure that detects and removes features in the measurement data that are inconsistent with the simulation responses. The complete paper describes formulation of the problem of updating S-curves with measurement data.

Neutron star mass and radius measurements from atmospheric model fits to X-ray burst cooling tail spectra

Observations of thermonuclear X-ray bursts from accreting neutron stars (NSs) in low-mass X-ray binary systems can be used to constrain NS masses and radii. Most previous work of this type has set these constraints using Planck function fits as a proxy: both the models and the data are fit with diluted blackbody functions to yield normalizations and temperatures which are then compared against each other. Here, for the first time, we fit atmosphere models of X-ray bursting NSs directly to the observed spectra. We present a hierarchical Bayesian fitting framework that uses state-of-the-art X-ray bursting NS atmosphere models with realistic opacities and relativistic exact Compton scattering kernels as a model for the surface emission. We test our approach against synthetic data, and find that for data that are well-described by our model we can obtain robust radius, mass, distance, and composition measurements. We then apply our technique to Rossi X-ray Timing Explorer observations of five hard-state X-ray bursts from 4U 1702-429. Our joint fit to all five bursts shows that the theoretical atmosphere models describe the data well but there are still some unmodeled features in the spectrum corresponding to a relative error of 1-5% of the energy flux. After marginalizing over this intrinsic scatter, we find that at 68% credibility the circumferential radius of the NS in 4U 1702-429 is R = 12.4+-0.4 km, the gravitational mass is M=1.9+-0.3 Msun, the distance is 5.1 < D/kpc < 6.2, and the hydrogen mass fraction is X < 0.09.

Abstract PR12: A model of HGF and EGF dual ligand stimulation in ACHN cells constructed with the aid of a novel model merging heuristic

Abstract The investigation of context-specific perturbations of cell signaling pathways requires the construction of large scale network models of multiple interacting pathways. A key issue in the production of these models is the process of model calibration, sometimes referred to as regression or optimization, during which parameters of a model are systematically adjusted to improve the model's predictions on a set of training data. We have developed a novel heuristic, termed “model merging,” to exploit parameter information from simpler models in the construction of new complex models. Using this merging heuristic, we developed a model of HGF and EGF stimulation of the MAP kinase cascade in ACHN cells, a renal cancer cell line. We constructed the model of HGF and EGF stimulation by first constructing smaller models of stimulation by each separate ligand. We use the single ligand models to inform the training of the dual ligand model by applying the model merging heuristic. Our model accurately reflects the time courses of pMET, pEGFR, and pMAPK under single ligand and dual ligand stimulation over two-hour time courses. It also captures several previously unmodeled features of MET and EGFR pathway crosstalk. The goal of model merging is to resolve parameter differences while maintaining the predictive quality of the previously known models. By the nature of model calibration, there are discrepancies between parameter estimates of the single ligand models whenever a parameter appears in both models. We design a scoring system for model predictions that takes into account the discrepancies between the parameter estimates. To resolve these discrepancies, our model merging heuristic iteratively adjusts the scoring system to create a series of optimization problems. The solutions to the series of problems converge to a resolved parametrization for the general model while maintaining the high quality of predictions of the component models. A key advantage of our heuristic over other model calibration algorithms is its ability to identify context-specific differences in parametrizations during model calibration. This is possible because the heuristic does not enforce any context-specific or context-free assumptions. Rather, it tries to resolve differences between multiple parameter sets by searching for a single consensus parameter set. If the training data precludes such a consensus for some of the parameters, then the heuristic can identify these parameters and simultaneously resolve the other parameters for which there is a consensus. In this way, the heuristic identifies parameters that are context-specific. This major advantage of our model merging method was integral to our construction of a model of HGF and EGF stimulation of the MAP Kinase cascade in ACHN cells. We identify context-specific parameters that describe a previously known, receptor-specific difference in phospho-MAPK negative feedback to the adapter protein GAB1. Identification of context-specific parametrizations also demonstrated that a prior model of EGF stimulated MAP kinase signaling employed an overly simplified mechanism of phospho-MAPK negative feedback to the protein SOS. Using this more detailed mechanism, we are now able to better interrogate the role of MAPK negative feedback in the more general multipathway setting. We also investigated the generalizability of our model merging heuristic by applying it repeatedly to a simplified version of our dual ligand model. We demonstrate that applying model merging in combination with Nelder-Mead calibration generates a significantly more robust estimation of parameters than Nelder-Mead calibration alone. Model merging thus produces a higher likelihood of finding a global best model parametrization instead of a local best parametrization. These results highlight the potential for our model merging technique to enable the creation of multipathway models with high mechanistic detail with reduced computational cost. This proffered talk is also presented as Poster A10. Citation Format: Andrew L. Matteson. A model of HGF and EGF dual ligand stimulation in ACHN cells constructed with the aid of a novel model merging heuristic [abstract]. In: Proceedings of the AACR Special Conference on Chemical Systems Biology: Assembling and Interrogating Computational Models of the Cancer Cell by Chemical Perturbations; 2012 Jun 27-30; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2012;72(13 Suppl):Abstract nr PR12.

THE EAST END, THE WEST END, AND KING'S CROSS: ON CLUSTERING IN THE FOUR‐PLAYER HOTELLING GAME

We study experimentally a standard four‐player Hotelling location game with a uniform density of consumers and inelastic demand. The pure strategy Nash equilibrium configuration consists of two firms located at one quarter of the “linear city,” and the other two at three quarters. We do not observe convergence to such an equilibrium. In our experimental data we find three clusters. Besides the direct proximity of the two equilibrium locations, this concerns the focal midpoint. Moreover, we observe that whereas this midpoint appears to become more notable over time, other focal points fade away. We explain how these observations are related to best‐response dynamics, and to the fact that the players rely on best‐responses in particular when they are close to the equilibrium configuration.

Coastal front tomography in the Haro Strait experiment: High resolution ray-based techniques

The coastal environment presents some unique challenges for ray-based acoustic tomography. The need to resolve travel time effects of environmental changes over smaller distance scales pushes the experiment designer toward higher frequencies, but higher frequency signals are more susceptible to unmodeled features of the environment like surface and bottom roughness and micro-structure within the water column. At Haro Strait, it was found that these unmodeled features of the environment had a greater overall impact on the received acoustic signal than did the features of interest. Two techniques proved useful in improving the environmental estimates under these conditions. The first technique was a matched filtering of the received signal which emphasized those parts of the signal most sensitive to the environmental features of interest and least sensitive to unmodeled features of the environment. The second technique was adaptive repositioning of one of the tomography sources, made possible by mounting the source on an AUV. Tomographic resolution is dependent on the source/receiver geometry, and by repositioning a source, resolution can be concentrated at emerging features of interest. The improved resolution offered by these techniques is shown in the data from Haro Strait. [Work supported by ONR.]

Fault parameters and slip distribution of the 1915 Avezzano, Italy, earthquake derived from geodetic observations

AbstractThis paper analyzes static surface displacements associated with the Avezzano, Italy, earthquake (Ms = 6.9) of 13 January 1915. The Avezzano event locates on a shallow normal fault centered in the Apennine mountains near a Quaternary tectonic depression named “Conca del Fucino.” The 1915 earthquake is the only sizable event to have occurred in the area for at least a millennium, although many Holocene and Quaternary faults can be recognized in the field. Awareness of the seismic potential of the Fucino region has heightened in recent years with the outward expansion of metropolitan Rome (80 km southwest). Because of a fortuitous pre-earthquake leveling survey near the fault in the mid 19th century, good quality geodetic data exist that illuminate details of the 1915 rupture. We modeled the faulting using both uniform (USP) and variable (VSP) slip planar dislocations. The best fitting focal mechanism includes pure dip slip on a plane striking 135° and plunging 63° to the southwest. This fault geometry is consistent with surface scarps and the broad scale tectonics of the region and is common to several large earthquakes of the south-central Apennines. The USP analysis estimates fault length, width, slip and moment to be 24 km, 15 km, 83 cm, and 9.7 × 1018 N-m, respectively. Numerical simulations indicate that residuals left in the uniform slip model are not entirely random and represent systematically unmodeled features of fault slip. VSP models of the earthquake significantly reduce the USP variance and reveal a broad two-lobed slip pattern, separating a central region of low moment release. New formulations detailing the relationships between VSP and minimum model norm solutions to underdetermined inverse problems are presented as well as concise statements dealing with the intrinsic and combined resolving power of a geodetic network.

An aperture synthesis study of Saturn and its rings at 3.71-cm wavelength

We present aperture synthesis maps of the Saturn system at a wavelength of 3.71 cm. The data used to make the maps were obtained in May–June 1976 at the Owens Valley Radio Observatory on 13 interferometer baselines. The aperture synthesis maps contain few assumptions about the brightness structure of Saturn and the rings and, therefore, may be used to check previous model-fitting results as well as search for new unmodeled features. Generally, the maps confirm the previous model-fitting results. An exception to this is that the brightness temperature of the planet that is implied by the maps is about 4% less than that deduced from model fitting. The likely explanation of this discrepancy is that random errors on the phase of the visibility function have led to an underestimate of the planet brightness temperature in the map. Maps of the residuals to the model fits have shown that the position of Saturn given in the American Ephemeris and Nautical Almanac may be in error by about 0.25 arcsec. Maps of the residuals to model fits including a position offset show that no new features of the Saturn brightness structure are required to match the present data. In particular, no azimuthal variations in the brightness temperature of the rings were detected.