Modeling and Identification of Position and Temperature Dependent Friction Phenomena without Temperature Sensing

This paper investigates both positional dependence in systems with friction and the influence an increase in temperature has on the friction behavior. The positional dependence is modeled with a Radial Basis Function network and the temperature dependence is modeled as a first order system with the power loss due to friction as input, eliminating the need for temperature sensing. The proposed methods are evaluated in both simulations and experiments on two industrial robots with strong positional and temperature friction dependence

Identification of LTV Dynamical Models with Smooth or Discontinuous Time Evolution by means of Convex Optimization

We establish a connection between trend filtering and system identification which results in a family of new identification methods for linear, time-varying (LTV) dynamical models based on convex optimization. We demonstrate how the design of the cost function promotes a model with either a continuous change in dynamics over time, or causes discontinuous changes in model coefficients occurring at a finite (sparse) set of time instances. We further discuss the introduction of priors on the model parameters for situations where excitation is insufficient for identification. The identification problems are cast as convex optimization problems and are applicable to, e.g., ARX models and state-space models with time-varying parameters. We illustrate usage of the methods in simulations of jump-linear systems, a nonlinear robot arm with non-smooth friction and stiff contacts as well as in model-based, trajectory centric reinforcement learning on a smooth nonlinear system

Two-Degree-of-Freedom Control for Trajectory Tracking and Perturbation Recovery during Execution of Dynamical Movement Primitives

Modeling of robot motion as dynamical movement primitives (DMPs) has becomean important framework within robot learning and control. The ability of DMPs to adapt online with respect to the surroundings, e.g., to moving targets, has been used and developed by several researchers. In this work, a method for handling perturbations during execution of DMPs on robots was developed. Two-degree-of-freedom control was introduced in the DMP context, for reference trajectory tracking and perturbation recovery. Benefits compared to the state of the art were demonstrated. The functionality of the method was verified in simulations and in real-world experiments

Make Research Data Public? -- Not Always so Simple: A Dialogue for Statisticians and Science Editors

Putting data into the public domain is not the same thing as making those data accessible for intelligent analysis. A distinguished group of editors and experts who were already engaged in one way or another with the issues inherent in making research data public came together with statisticians to initiate a dialogue about policies and practicalities of requiring published research to be accompanied by publication of the research data. This dialogue carried beyond the broad issues of the advisability, the intellectual integrity, the scientific exigencies to the relevance of these issues to statistics as a discipline and the relevance of statistics, from inference to modeling to data exploration, to science and social science policies on these issues.Comment: Published in at http://dx.doi.org/10.1214/10-STS320 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Robotic friction stir welding—Seam-tracking control, force control and process supervision

Purpose – This study aims to enable robotic friction stir welding (FSW) in practice. The use of robots has hitherto been limited, because of the large contact forces necessary for FSW. These forces are detrimental for the position accuracy of the robot. In this context, it is not sufficient to rely on the robot’s internal sensors for positioning. This paper describes and evaluates a new method for overcoming this issue.Design/methodology/approach – A closed-loop robot control system for seam-tracking control and force control, running and recording data in real-time operation, was developed. The complete system was experimentally verified. External position measurements were obtained from a laser seam tracker and deviations from the seam were compensated for, using feedback of the measurements to a position controller.Findings – The proposed system was shown to be working well in overcoming position error. The system is flexible and reconfigurable for batch and short production runs. The welds were free of defects and had beneficial mechanical properties.Research limitations/implications – In the experiments, the laser seam tracker was used both for control feedback and for performance evaluation. For evaluation, it would be better to use yet another external sensor for position measurements, providing ground truth.Practical implications – These results imply that robotic FSW is practically realizable, with the accuracy requirements fulfilled.Originality/value – The method proposed in this research yields very accurate seam tracking as compared to previous research. This accuracy, in turn, is crucial for the quality of the resulting material.Keywords Friction stir welding, Robotics, Force control, Seam-tracking control, Control, Sensors, Robot weldin

Rat Strain Differences in Susceptibility to Alcohol-Induced Chronic Liver Injury and Hepatic Insulin Resistance

The finding of more severe steatohepatitis in alcohol fed Long Evans (LE) compared with Sprague Dawley (SD) and Fisher 344 (FS) rats prompted us to determine whether host factors related to alcohol metabolism, inflammation, and insulin/IGF signaling predict proneness to alcohol-mediated liver injury. Adult FS, SD, and LE rats were fed liquid diets containing 0% or 37% (calories) ethanol for 8 weeks. Among controls, LE rats had significantly higher ALT and reduced GAPDH relative to SD and FS rats. Among ethanol-fed rats, despite similar blood alcohol levels, LE rats had more pronounced steatohepatitis and fibrosis, higher levels of ALT, DNA damage, pro-inflammatory cytokines, ADH, ALDH, catalase, GFAP, desmin, and collagen expression, and reduced insulin receptor binding relative to FS rats. Ethanol-exposed SD rats had intermediate degrees of steatohepatitis, increased ALT, ADH and profibrogenesis gene expression, and suppressed insulin receptor binding and GAPDH expression, while pro-inflammatory cytokines were similarly increased as in LE rats. Ethanol feeding in FS rats only reduced IL-6, ALDH1–3, CYP2E1, and GAPDH expression in liver. In conclusion, susceptibility to chronic steatohepatitis may be driven by factors related to efficiency of ethanol metabolism and degree to which ethanol exposure causes hepatic insulin resistance and cytokine activation

Anti-Tumor Effects of Second Generation β-Hydroxylase Inhibitors on Cholangiocarcinoma Development and Progression

Cholangiocarcinoma (CCA) has a poor prognosis due to widespread intrahepatic spread. Aspartate β-hydroxylase (ASPH) is a transmembrane protein and catalyzes the hydroxylation of aspartyl and asparaginyl residues in calcium binding epidermal growth factor (cbEGF)-like domains of various proteins, including Notch receptors and ligands. ASPH is highly overexpressed (\u3e95%) in human CCA tumors. We explored the molecular mechanisms by which ASPH mediated the CCA malignant phenotype and evaluated the potential of ASPH as a therapeutic target for CCA. The importance of expression and enzymatic activity of ASPH for CCA growth and progression was examined using shRNA “knockdown” and a mutant construct that reduced its catalytic activity. Second generation small molecule inhibitors (SMIs) of β-hydroxylase activity were developed and used to target ASPH in vitro and in vivo. Subcutaneous and intrahepatic xenograft rodent models were employed to determine anti-tumor effects on CCA growth and development. It was found that the enzymatic activity of ASPH was critical for mediating CCA progression, as well as inhibiting apoptosis. Mechanistically, ASPH overexpression promoted Notch activation and modulated CCA progression through a Notch1-dependent cyclin D1 pathway. Targeting ASPH with shRNAs or a SMI significantly suppressed CCA growth in vivo