Inexact Models Research Articles

Approaches based on LAMDA control applied to regulate HVAC systems for buildings

The control of HVAC (Heating Ventilation and Air Conditioning) systems is usually complex because its modeling in certain cases is difficult, since these systems have a large number of components. Heat exchangers, chillers, valves, sensors, and actuators, increase the non-linear characteristics of the complete model, so it is necessary to propose new control strategies that can handle the uncertainty generated by all these elements working together. On the other hand, artificial intelligence is a powerful tool that allows improving the performance of control systems with inexact models and uncertainties. This paper presents new control alternatives for HVAC systems based on LAMDA (Learning Algorithm for Multivariable Data Analysis). This algorithm has been used in the field of machine learning, however, we have taken advantage of its learning characteristics to propose different types of intelligent controllers to improve the performance of the overall control system in tasks of regulation and reference change. In order to perform a comparative analysis in the context of HVAC systems, conventional methods such as PID and Fuzzy-PID are compared with LAMDA-PID, LAMDA-Sliding Mode Control based on Z-numbers (ZLSMC), and Adaptive LAMDA. Specifically, two HVAC systems are implemented by simulations to evaluate the proposals: an MIMO (Multiple-input Multiple-output) HVAC system and an HVAC system with dead time, which are used to compare the results qualitatively and quantitatively. The results show that ZLSMC is the most robust controller, which efficiently controls HVAC systems in cases of reference changes and the presence of disturbances.

Useful Untruths: Another Look at Pluralism in the Clinical Setting

Hans Vaihinger, the early 20th Century German philosopher, contended that across a broad range of thought people tend to select one theory over others, all the while knowing that such a singular perspective is but an idealization or useful fiction of what the fuller truth is if one eventually includes those other theories. He argued for the necessity of utilizing a plurality of perspectives in order to see a more complete picture of the world despite our cognitive inability to juggle more than one theory at the same time. This vexing paradox is a focus of the contemporary philosopher Kwame Anthony Appiah’s recent work that pays tribute to Vaihinger’s exploration of this topic. Appiah also examines Vaihinger’s view that hewing to a single fiction at certain times and for certain reasons is useful, while also considering how to expand one’s scope to reach for a more inclusive multiplicity of inexact models. I apply these and related issues to the psychoanalytic clinical situation, addressing such matters as: the possible triggers for the analyst’s shifts toward alternate theoretical persuasions and the complex matter of truth.

Generalized Information

Generalized Information (GI) is a measurement of the degree to which a program can be said to generalize a dataset. It is calculated by creating a program to model the data set, measuring the Active Information in the model, and subtracting out the size of the model. Active Information allows GI to be usable with both exact and inexact models.

Computer Model Calibration with Confidence and Consistency

SummaryThe paper proposes and examines a calibration method for inexact models. The method produces a confidence set on the parameters that includes the best parameter with a desired probability under any sample size. Additionally, this confidence set is shown to be consistent in that it excludes suboptimal parameters in large sample environments. The method works and the results hold with few assumptions; the ideas are maintained even with discrete input spaces or parameter spaces. Computation of the confidence sets and approximate confidence sets is discussed. The performance is illustrated in a simulation example as well as two real data examples.

Interval joint-probabilistic chance-constrained programming with two-side multi-randomness: an application to energy-environment systems management

Regional energy-environment systems management become more and more focused on greenhouse gas emission control through improving energy efficiency and efficiently managing energy activities. Inexact linear programming models are developed for supporting the management. Due to the weather/climatic variations in the future, electricity demands and renewable power generations (in the right/left hand sides of constraints) have random characteristics. Moreover, an overall satisfactory level needs to be quantified based on multiple chance constraints. Therefore, this study improved upon traditional chance-constrained programming and interval linear programming, and developed an interval joint-probabilistic two-side chance-constrained programming (IJTCP) approach. A sufficient but non-equivalent linearization form of the model was proposed so that the inexact model could be solved through the two-step solution algorithm. The IJTCP was then applied to an integrated energy-environment systems management under dual uncertainties. The application demonstrated that the IJTCP can effectively address the uncertainties presented as not only interval numbers and two-side multi-randomness but also the reliability of satisfying the entire system constraints. The application implicated that the IJTCP approach can be applied to other energy-environment management problems under dual uncertainties.

Hardware Inexact Grammar Parser

In this paper, a platform is presented, that given a Stochastic Context-Free Grammar (SCFG), automatically outputs the description of a parser in synthesizable Hardware Description Language (HDL) which can be downloaded in an FPGA (Field Programmable Gate Arrays) board. Although the proposed methodology can be used for various inexact models, the probabilistic model is analyzed in detail and the extension to other inexact schemes is described. Context-Free Grammars (CFG) are augmented with attributes which represent the probability values. Initially, a methodology is proposed based on the fact that the probabilities can be evaluated concurrently with the parsing during the parse table construction by extending the fundamental parsing operation proposed by Chiang & Fu. Using this extended operation, an efficient architecture is presented based on Earley’s parallel algorithm, which given an input string, generates the parse table while evaluating concurrently the probabilities of the generated dotted grammar rules in the table. Based on this architecture, a platform has been implemented that automatically generates the hardware design of the parser given a SCFG. The platform is suitable for embedded systems applications where a natural language interface is required or in pattern recognition tasks. The proposed hardware platform has been tested for various SCFGs and was compared with previously presented hardware parser for SCFGs based on Earley’s parallel algorithm. The hardware generated by the proposed platform is much less complicated than the one of comparison and succeeds a speed-up of one order of magnitude.

An Interval Approach for Robust Control of a Large PHWR with PID Controllers

A nuclear reactor exhibits changing behavior with variation in reactor power. Further, uncertainties in the measurement of the actual power produced by the reactor, the heat transfer from the fuel to the coolant and the reactivity change due to the change in the fuel and coolant temperatures and condition of the core, make it necessary to adopt a robust control approach for design of control systems for such plants. In this paper a 540 MWe Indian PHWR consisting of 14 zones has been modeled using inexact models incorporating bounded parametric variations in power, heat transfer from the fuel to the coolant and temperature coefficients of reactivity of fuel and coolant. These inexact models are then used to obtain a robust and optimal PID controller gains for controlling the reactor power with specified time response under parametric variations, using an interval approach. The methodology is established with credible MATLAB simulations.

Iterative Frequency-Weighted Filtering and Smoothing Procedures

Minimum-variance filters and smoothers exhibit performance degradations when they are designed with inexact models and noise statistics. Filter and smoother estimation errors are assumed herein to be generated by a first-order moving-average system. This assumed system is identified and used to design a frequency weighting function to improve mean square error performance. It is shown under prescribed conditions that the sequence of frequency-weighted estimation error variances are nonincreasing. An example is presented which demonstrates the efficacy of repeated frequency weighting iterations.

Some exact and inexact linear rational expectation models in vector autoregressive models

In this paper we consider maximum likelihood estimation in some exact and inexact linear rational expectation (LRE) models. The implications of the two models on the coefficients of the vector autoregressive (VAR) model are spelled out. The inexact version is more complicated and possible simplification of the resulting constrained optimization problem is discussed.

Partitioned Analysis of Coupled Numerical Models Considering Imprecise Parameters and Inexact Models

The present study develops an integrated coupling and uncertainty quantification framework for strongly coupled models that explicitly considers the propagation of uncertainty and bias inherent in model prediction between constituents during the iterative coupling process. Utilizing optimization techniques, three distinct configurations are formulated that differ in sequence of coupling and uncertainty quantification campaigns. Focusing on a controlled structural dynamics problem, the systematic biases from the constituents are quantified, from which the critical components of the model that require further improvement can be identified to aid in the prioritization of future code development efforts. DOI: 10.1061/(ASCE)CP.1943-5487.0000253. © 2014 American Society of Civil Engineers. Author keywords: Coupled simulations; Optimization; Uncertainty propagation; Discrepancy-Bias; Model calibration; Partitioned analysis.

Sensitivity of beamformer source analysis to deficiencies in forward modeling

Event Abstract Back to Event Sensitivity of beamformer source analysis to deficiencies in forward modeling Olaf Steinstraeter1*, Stephanie Sillekens1, Markus Junghoefer1, Martin Burger2 and Carsten Wolters1 1 University of Muenster, Institute for Biomagnetism and Biosignalanalysis, Germany 2 University of Muenster, Institute for Computational and Applied Mathematics, Germany Beamforming approaches recently developed for the electro- (EEG) and magnetoencephalography (MEG) source analysis are already widely used. Nevertheless, some fundamental methodological aspects are still quite unclear. Here, we present a systematic study on the influence of improper volume conductor modeling on the source reconstruction performance of an EEG-data driven synthetic aperture magnetometry (SAM) beamforming approach. Simulations were based on a detailed realistically-shaped three-layer (skin, skull, brain) finite element (FE) model of a human head derived from multimodal MR images. Different models for the skull conductivity were used to investigate anisotropy effects. A spherical head model was fitted to study the influence of geometrical misspecifications. The SAM reconstructions were based on pseudo-Z values. Localization errors up to 37 mm were found with a spatial distribution depending on the geometric deviations to the exact model: local differences to spherical shape (spherical head model), local skull thickness. The effect of scull anisotropy was dominated by the radial skull component of the conductivity tensor. By using the exact volume conductor model, the distribution of amplitude and width of the SAM peaks reflected the local signal-to-noise ratio of the sources (pseudo-Z values). For inexact models we found large differences depending on the noise level: The influence of the model differences to amplitude and width of the peaks was large for low noise but less important for higher noise levels. We conclude that depending on source position and sensor coverage, deficiencies in volume conductor modeling might lead to localization errors up to several centimeters. The spatial distribution of peak amplitude and width, important for the assessment of the local relevance of beamformer results, strongly depends on the noise level in the case of inaccurate volume conductor models and becomes nearly unpredictable if the signal-to-noise ratio is high. Conference: Biomag 2010 - 17th International Conference on Biomagnetism , Dubrovnik, Croatia, 28 Mar - 1 Apr, 2010. Presentation Type: Poster Presentation Topic: MEG Modeling Citation: Steinstraeter O, Sillekens S, Junghoefer M, Burger M and Wolters C (2010). Sensitivity of beamformer source analysis to deficiencies in forward modeling. Front. Neurosci. Conference Abstract: Biomag 2010 - 17th International Conference on Biomagnetism . doi: 10.3389/conf.fnins.2010.06.00051 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 21 Mar 2010; Published Online: 21 Mar 2010. * Correspondence: Olaf Steinstraeter, University of Muenster, Institute for Biomagnetism and Biosignalanalysis, Muenster, Germany, Olaf.Steinstraeter@uni-muenster.de Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Olaf Steinstraeter Stephanie Sillekens Markus Junghoefer Martin Burger Carsten Wolters Google Olaf Steinstraeter Stephanie Sillekens Markus Junghoefer Martin Burger Carsten Wolters Google Scholar Olaf Steinstraeter Stephanie Sillekens Markus Junghoefer Martin Burger Carsten Wolters PubMed Olaf Steinstraeter Stephanie Sillekens Markus Junghoefer Martin Burger Carsten Wolters Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

Brain, symbol & experience: toward a neurophenomenology of human consciousness

Laughlin et al. show that ongoing experience is mediated by the brain and that competing networks are constantly and re-entrained, thereby providing inexact models of ourselves and the world. Phases of neural entrainments...punctuated by...rapid periods of reentrainments...organized about some object are the structure of consciousness (neurological factors), while behavioural expressions of consciousness involve manipulation of because society must assure that proper associations are entrained (cultural factors). Experiences of consciousness consist of sensations that penetrate entrainments thereby reaching consciousness (internal factors, such as altered states and dreams). Rituals and cosmology are penetration devices that stimulate...a...theatre of mind and provide meaning for individuals (p. 335). Our being, therefore, is community of cells (pp. 34, 334) and we are symbols to each other (p. 232). This brief summary does not do justice to complex ideas. Laudable is the holistic approach the authors advocate and try to achieve. Nevertheless, women's work, experiences, and bodies are consistently ignored and, when gender is discussed, it is from a male perspective. For example, the authors claim that there was no field work before Malinowski (p. 23), but Alice Fletcher and Harriet Martineau were early ethnographers urging field work (S. Reinharz, Feminist Methods in Social Research [Oxford University Press, 1992], pp. 49-50). Patriarchal systems, ideologies and male practitioners are used to illustrate arguments. For instance, male shamans during their magical flight are said to experience a female psychopomp (p. 273), but female shamanistic knowledge is left unexplored. Cross-cultural examples mention only one female yogi (p. 311) and the only Western female considered subscribed to a patriarchal framework (p. 307). Discussion of Tibetan Buddhism is also strictly from a male perspective since Tibetan women's views of their wombs, energies and consciousness are not contemplated (pp. 206-210, 351). Male bias is also expressed in interpretations of Tibetan Buddhist art in that the woman is viewed as having intuitive knowledge, as dangerous, as having raw energy and as vulnerable and submissive, while the man is portrayed as having conceptual knowledge, as grounded, non-attached and dependent on her energy (pp. 208, 209). She is said to come from nothingness, to give men energy and to return to nothingness (p. 351). All cosmologies are seen by the authors as somatocentric (p. 225) and through relationships within the body the entire cosmos is supposed to be known (p. 226). If metaphors are based on male bodies only, then the nature of the entire cosmos is now known. Claims to universality are on shaky grounds when women's experiences are ignored, while male knowledge is used to buttress arguments and gender-inappropriate language is employed throughout (pp. 226-341). Although the authors strongly criticize positivism (pp. 338-346) and call for a holistic and experiential science, feminist scholarship that criticizes positivism and supports experiential science is nowhere acknowledged. While Laughlin et al. attend to culture neurologically, some authors in Schwartz et al. approach the brain culturally. White explores ethnopsychology while D'Andrade, Keller and Holland discuss simplified knowledge structures (schemata) that, according to D'Andrade, provide direct access to psychological processes. As he calls for descriptions of people (p. 56), it seems that schema theory is again an attempt to reduce human complexities to one denominator while re-labelling national character studies. Keller also appears to favour simpler levels, while Holland illustrates that schema theory cannot deal with multiple interpretations, negotiation, conflict, power and cognitive self-censorship. …

The Hamiltonian structure of nonlinear elasticity: The material and convective representations of solids, rods, and plates

It is our belief that a thorough understanding of the mathematical underpinnings of elasticity is crucial to its analytical and numerical implementation. For example, in the analysis of rotating structures, the coupling of the equations for geometrically inexact models, obtained by linearization or other approximations, with those for rotating rigid bodies can easily lead to misleading artificial “softening” effects that can significantly alter numerical results; see Simo and VuQuoc [1986c] (especially equations (3) and (5)). In this paper, we consider fully nonlinear geometrically exact models for rods, plates (and shells) which take into account shear and torsion as well as the usual bending effects in traditional rod and plate models. These models can be obtained either from the three-dimensional theory by a systematic use of projection methods; see e.g., Antman [1972] and Naghdi [1972], or by a direct approach within the context of Cosserat continuum. Remarkably, the two approaches lead to essentially the same form of the governing field equations. In the present context, we have chosen as a model problem a particular rod model which may be regarded as an extension of the classical Kirchhoff-Love model (see Love [1944]) to include shear deformations, as in

Wmatrix and the geometry of model equivalence and reduction

The wmatrix is shown to contain valuable information on the geometry of the dynamical behaviour of linear dynamical systems. Certain known results involving the wmatrix and new results, which demonstrate the importance of the Wmatrix in the equivalence and reduction of models, are presented.The concept of best subspaces is central to the problem of model reduction. It is shown that, for impulse inputs, the best subspace may be specified in terms of the eigenstructure of tne Wmatrix.The conditioning of a system is defined and investigated, and it is found to be determined by the W matrix.For white Gaussian noise disturbances, the correlation ellipsoid is defined and is given in terms of the Wmatrix. The best subspaces are reinterpreted in terms of the correlation ellipsoid. The minimum variance estimation problem in the context of inexact models is considered. Finally, an information theoretic functional for the model reduction problem is investigated.