926 resultados para Model Identification
Resumo:
Several mobile robots show non-linear behavior, mainly due friction phenomena between the mechanical parts of the robot or between the robot and the ground. Linear models are efficient in some cases, but it is necessary take the robot non-linearity in consideration when precise displacement and positioning are desired. In this work a parametric model identification procedure for a mobile robot with differential drive that considers the dead-zone in the robot actuators is proposed. The method consists in dividing the system into Hammerstein systems and then uses the key-term separation principle to present the input-output relations which shows the parameters from both linear and non-linear blocks. The parameters are then simultaneously estimated through a recursive least squares algorithm. The results shows that is possible to identify the dead-zone thresholds together with the linear parameters
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Alternans of cardiac action potential duration (APD) is a well-known arrhythmogenic mechanism which results from dynamical instabilities. The propensity to alternans is classically investigated by examining APD restitution and by deriving APD restitution slopes as predictive markers. However, experiments have shown that such markers are not always accurate for the prediction of alternans. Using a mathematical ventricular cell model known to exhibit unstable dynamics of both membrane potential and Ca2+ cycling, we demonstrate that an accurate marker can be obtained by pacing at cycle lengths (CLs) varying randomly around a basic CL (BCL) and by evaluating the transfer function between the time series of CLs and APDs using an autoregressive-moving-average (ARMA) model. The first pole of this transfer function corresponds to the eigenvalue (λalt) of the dominant eigenmode of the cardiac system, which predicts that alternans occurs when λalt≤−1. For different BCLs, control values of λalt were obtained using eigenmode analysis and compared to the first pole of the transfer function estimated using ARMA model fitting in simulations of random pacing protocols. In all versions of the cell model, this pole provided an accurate estimation of λalt. Furthermore, during slow ramp decreases of BCL or simulated drug application, this approach predicted the onset of alternans by extrapolating the time course of the estimated λalt. In conclusion, stochastic pacing and ARMA model identification represents a novel approach to predict alternans without making any assumptions about its ionic mechanisms. It should therefore be applicable experimentally for any type of myocardial cell.
Resumo:
This report presents the proceedings of the Biochemical Engineering Symposium held at Kansas State University, June 4, 1971. Since most of the papers will be published elsewhere, only very brief papers are included here. Moreover, several of the projects are still in progress at this time. Request for additional information on projects conducted at the University of Nebraska should be directed to Dr. Peter J. Reilly and for Kansas State University to Dr. L. E. Erickson. ContentsChao, Chih-Cheng, University of Nebraska, "Symbiotic Growth of Actobacter suboxydans and Saccharomyces carlsbergensis in a Chemostat" S.Y. Chiu, Kansas State University, "Model Identification in Mixed Populations Using Continuous Culture Data" Shinji Goto, University of Nebraska, "Symbiotic Growth of Bacteria and Blue Green Algae in a Chemostat" I.C. Kao, Kansas State University, "ATP as a Parameter of Mixed Culture Interaction" Indravadan R. Kothari, University of Nebraska, "Growth of Single Cells of Schizocaccharomyces pombe under Nutrient Limitation" G.C.Y. Chu, Kansas State University, "Experimental Optimization of Biological Waste Treatment Processes" Mark Young, University of Nebraska, "Aerobic Fermentation of Paunch Liquor" P.S. Shah, Kansas State University, "Optimal Control of Growth Processes"
Resumo:
In situ diffusion experiments are performed in geological formations at underground research laboratories to overcome the limitations of laboratory diffusion experiments and investigate scale effects. Tracer concentrations are monitored at the injection interval during the experiment (dilution data) and measured from host rock samples around the injection interval at the end of the experiment (overcoring data). Diffusion and sorption parameters are derived from the inverse numerical modeling of the measured tracer data. The identifiability and the uncertainties of tritium and Na-22(+) diffusion and sorption parameters are studied here by synthetic experiments having the same characteristics as the in situ diffusion and retention (DR) experiment performed on Opalinus Clay. Contrary to previous identifiability analyses of in situ diffusion experiments, which used either dilution or overcoring data at approximate locations, our analysis of the parameter identifiability relies simultaneously on dilution and overcoring data, accounts for the actual position of the overcoring samples in the claystone, uses realistic values of the standard deviation of the measurement errors, relies on model identification criteria to select the most appropriate hypothesis about the existence of a borehole disturbed zone and addresses the effect of errors in the location of the sampling profiles. The simultaneous use of dilution and overcoring data provides accurate parameter estimates in the presence of measurement errors, allows the identification of the right hypothesis about the borehole disturbed zone and diminishes other model uncertainties such as those caused by errors in the volume of the circulation system and the effective diffusion coefficient of the filter. The proper interpretation of the experiment requires the right hypothesis about the borehole disturbed zone. A wrong assumption leads to large estimation errors. The use of model identification criteria helps in the selection of the best model. Small errors in the depth of the overcoring samples lead to large parameter estimation errors. Therefore, attention should be paid to minimize the errors in positioning the depth of the samples. The results of the identifiability analysis do not depend on the particular realization of random numbers. (C) 2012 Elsevier B.V. All rights reserved.
Resumo:
This study provides a review of the current alcoholism planning process of the Houston-Galveston planning process of the Houston-Galveston Area Council, an agency carrying out planning for a thirteen county region in surrounding Houston, Texas. The four central groups involved in this planning are identified, and the role that each plays and how it effects the planning outcomes is discussed.^ The most substantive outcome of the Houston-Galveston Area Council's alcoholism planning, the Regional Alcoholism/Alcohol Abuse Plan is examined. Many of the shortcomings in the data provided, and the lack of other data necessary for planning are offered.^ A problem oriented planning model is presented as an alternative to the Houston-Galveston Area Council's current service oriented approach to alcoholism planning. Five primary phases of the model, identification of the problem, statement of objectives, selection of alternative programs, implementation, and evaluation, are presented, and an overview of the tasks involved in the application of this model to alcoholism planning is offered.^ A specific aspect of the model, the use of problem status indicators is explored using cirrhosis and suicide mortality data. A review of the literature suggests that based on five criteria, availability, subgroup identification, validity, reliability, and sensitivity, both suicide and cirrhosis are suitable as indicators of the alcohol problem when combined with other indicators.^ Cirrhosis and suicide mortality data are examined for the thirteen county Houston-Galveston Region for the years 1969 through 1976. Data limitations preclude definite conclusions concerning the alcohol problem in the region. Three hypotheses about the nature of the regional alcohol problem are presented. First, there appears to be no linear trend in the number of alcoholics that are at risk of suicide and cirrhosis mortality. Second, the number of alcoholics in the metropolitan areas seems to be greater than the number of rural areas. Third, the number of male alcoholics at risk of cirrhosis and suicide mortality is greater than the number of female alcoholics.^
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Delamination reduces the strenght of the composites, mainly in compression. Several methods exist to overcome this problem, but they are either not feasible for large scale production or too expensive. 3D composites are a promising solution.
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In this paper, a new control design method is proposed for stable processes which can be described using Hammerstein-Wiener models. The internal model control (IMC) framework is extended to accommodate multiple IMC controllers, one for each subsystem. The concept of passive systems is used to construct the IMC controllers which approximate the inverses of the subsystems to achieve dynamic control performance. The Passivity Theorem is used to ensure the closed-loop stability. (c) 2005 Elsevier Ltd. All rights reserved.
Resumo:
In enhanced biological phosphorus removal (EBPR) processes, glycogen-accumulating organisms (GAOs) may compete with polyphosphate-accumulating organisms (PAOs) for the often-limited carbon substrates, potentially resulting in disturbances to phosphorus removal. A detailed investigation of the effect of pH on the competition between PAOs and GAOs is reported in this study. The results show that a high external pH (similar to 8) provided PAOs with an advantage over GAOs in EBPR systems. The phosphorus removal performance improved due to a population shift favouring PAOs over GAOs, which was shown through both chemical and microbiological methods. Two lab-scale reactors fed with propionate as the carbon source were subjected to an increase in pH from 7 to 8. The phosphorus removal and PAO population (as measured by quantitative fluorescence in situ hybridisation analysis of Candidatus Accumulibacter phosphatis) increased in each system, where the PAOs appeared to out-compete a group of Alphaproteobacteria GAOs. A considerable improvement in the P removal was also observed in an acetate fed reactor, where the GAO population (primarily Candidatus Competibacter phosphatis) decreased substantially after a similar increase in the pH. The results from this study suggest that pH could be used as a control parameter to reduce the undesirable proliferation of GAOs and improve phosphorus removal in EBPR systems. (c) 2005 Elsevier Ltd. All rights reserved.
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The aim of this study was to explore two of the mechanisms by which transformational leaders have a positive influence on followers. It examined the mediating role of follower's leader and group identification on the associations among different transformational leader behaviours and follower job satisfaction and supervisor-rated job performance. One hundred and seventy-nine healthcare employees and 44 supervisors participated in the study. The results from multilevel structural equation modelling provided results that partially supported the predicted model. Identification with the leader significantly mediated the positive associations between supportive leadership, intellectual stimulation, personal recognition, in the prediction of job satisfaction and job performance. Leader identification also mediated the relationship between supportive leadership, intellectual stimulation, personal recognition, and group identification. However, group identification did not mediate the associations between vision leadership and inspirational communication, in the prediction of job satisfaction and job performance. The results highlight the role of individualized forms of leadership and leader identification in enhancing follower outcomes.
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The educational process is characterised by multiple outcomes such as the achievement of academic results of various standards and non-academic achievements. This paper shows how data envelopment analysis (DEA) can be used to guide secondary schools to improved performance through role-model identification and target setting in a way which recognises the multi-outcome nature of the education process and reflects the relative desirability of improving individual outcomes. The approach presented in the paper draws from a DEA-based assessment of the schools of a local education authority carried out by the authors. Data from that assessment are used to illustrate the approach presented in the paper. (Key words: Data envelopment analysis, education, target setting.)
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In collaboration with G.D. SpA I attended an internship with the purpose of developing a filter for the position control of industrial machines during testing and maintenance operations. The filter elaborates a signal in position provided by an electonic handwheel, in order to enable the application to be controlled with a signal in velocity with arbitrarily dynamics chosen during the design phase. Limiting the dynamics of the filter provide a more stable and less demanding reference trajectory which reduce the vibrations and tracking errors of the motor controlled by it. It also prevents misusages of the handwheel from the technician which could end up in harmful interferences between the mechanical parts moved by the handwheel.
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A way of coupling digital image correlation (to measure displacement fields) and boundary element method (to compute displacements and tractions along a crack surface) is presented herein. It allows for the identification of Young`s modulus and fracture parameters associated with a cohesive model. This procedure is illustrated to analyze the latter for an ordinary concrete in a three-point bend test on a notched beam. In view of measurement uncertainties, the results are deemed trustworthy thanks to the fact that numerous measurement points are accessible and used as entries to the identification procedure. (C) 2010 Elsevier Ltd. All rights reserved.
Resumo:
Among several process variability sources, valve friction and inadequate controller tuning are supposed to be two of the most prevalent. Friction quantification methods can be applied to the development of model-based compensators or to diagnose valves that need repair, whereas accurate process models can be used in controller retuning. This paper extends existing methods that jointly estimate the friction and process parameters, so that a nonlinear structure is adopted to represent the process model. The developed estimation algorithm is tested with three different data sources: a simulated first order plus dead time process, a hybrid setup (composed of a real valve and a simulated pH neutralization process) and from three industrial datasets corresponding to real control loops. The results demonstrate that the friction is accurately quantified, as well as ""good"" process models are estimated in several situations. Furthermore, when a nonlinear process model is considered, the proposed extension presents significant advantages: (i) greater accuracy for friction quantification and (ii) reasonable estimates of the nonlinear steady-state characteristics of the process. (C) 2010 Elsevier Ltd. All rights reserved.
Resumo:
This work deals with a procedure for model re-identification of a process in closed loop with ail already existing commercial MPC. The controller considered here has a two-layer structure where the upper layer performs a target calculation based on a simplified steady-state optimization of the process. Here, it is proposed a methodology where a test signal is introduced in a tuning parameter of the target calculation layer. When the outputs are controlled by zones instead of at fixed set points, the approach allows the continuous operation of the process without an excessive disruption of the operating objectives as process constraints and product specifications remain satisfied during the identification test. The application of the method is illustrated through the simulation of two processes of the oil refining industry. (c) 2008 Elsevier Ltd. All rights reserved.