Crumpling of a stiff tethered membrane

first-principles numerical simulation model for crumpling of a stiff tethered membrane is introduced. In our model membranes, wrinkles, ridge formation, ridge collapse, as well as the initiation of stiffness divergence, are observed. The ratio of the amplitude and wave length of the wrinkles, and the scaling exponent of the stiffness divergence, are consistent with both theory and experiment. We observe that close to the stiffness divergence there appears a crossover beyond which the elastic behavior of a tethered membrane becomes similar to that of dry granular media. This suggests that ridge formation in membranes and force-chain network formation in granular packings are different manifestations of a single phenomenon.Comment: For full resolution figures, please send us an emai

Some Practical Applications of Dark Matter Research

Two practical spin-offs from the development of cryogenic dark matter detectors are presented. One in materials research, the other in biology.Comment: 8 pages,4 figure

A Single-Loop DC Motor Control System Design with a Desired Aperiodic Degree of Stability

The application of the original analytical approach for Pi-controller synthesis of a stable second-order plant is considered. This approach allows finding controller parameters without any intensive computing by using the direct expressions. The plant model is obtained on the basis of identification, which is based on the automated real-interpolation method. The results of natural experiments are given

Active Learning in Persistent Surveillance UAV Missions

The performance of many complex UAV decision-making problems can be extremely sensitive to small errors in the model parameters. One way of mitigating this sensitivity is by designing algorithms that more effectively learn the model throughout the course of a mission. This paper addresses this important problem by considering model uncertainty in a multi-agent Markov Decision Process (MDP) and using an active learning approach to quickly learn transition model parameters. We build on previous research that allowed UAVs to passively update model parameter estimates by incorporating new state transition observations. In this work, however, the UAVs choose to actively reduce the uncertainty in their model parameters by taking exploratory and informative actions. These actions result in a faster adaptation and, by explicitly accounting for UAV fuel dynamics, also mitigates the risk of the exploration. This paper compares the nominal, passive learning approach against two methods for incorporating active learning into the MDP framework: (1) All state transitions are rewarded equally, and (2) State transition rewards are weighted according to the expected resulting reduction in the variance of the model parameter. In both cases, agent behaviors emerge that enable faster convergence of the uncertain model parameters to their true values

Measuring well-being in aphasia: The GHQ-28 versus the NHP

This study aimed to get the opinions of people with aphasia on two subjective well-being measures: the General Health Questionnaire 28-item version (GHQ-28) (Goldberg & Hillier, 1979) and the Nottingham Health Profile (NHP) (Hunt, McKenna, McEwen, Williams, & Papp, 1981). Twelve persons with moderate to mild aphasia of at least 2-years duration completed the GHQ-28 and the NHP. In a semistructured intenriew, they gave their feedback on the two questionnaires. All participants were able to complete both instruments. Nine out of 12 participants showed high psychological distress (> 5/28) in the GHQ-28. The NHP (part 1 less the physical abilities section) had a correlation of 0.78 (p < .01) with the GHQ-28. The social dysfunction subscale of the NHP identified more problems in the participants with aphasia than the social isolation subscale of the GHQ-28. The majority of the participants (10 out of 12) preferred the NHP, as they found it easier to understand and respond to. This small-scale study indicated that both the GHQ-28 and the NHP can be administered to people with moderate to mild aphasia and provide useful information on their well-being. Participants reported that the NHP was easier to do, and it asked questions more relevant to their situation

Resilient Parameter-Invariant Control With Application to Vehicle Cruise Control

This work addresses the general problem of resilient control of unknown stochastic linear time-invariant (LTI) systems in the presence of sensor attacks. Motivated by a vehicle cruise control application, this work considers a first order system with multiple measurements, of which a bounded subset may be corrupted. A frequency-domain-designed resilient parameter-invariant controller is introduced that simultaneously minimizes the effect of corrupted sensors, while maintaining a desired closed-loop performance, invariant to unknown model parameters. Simulated results illustrate that the resilient parameter-invariant controller is capable of stabilizing unknown state disturbances and can perform state trajectory tracking

Ball on a beam: stabilization under saturated input control with large basin of attraction

This article is devoted to the stabilization of two underactuated planar systems, the well-known straight beam-and-ball system and an original circular beam-and-ball system. The feedback control for each system is designed, using the Jordan form of its model, linearized near the unstable equilibrium. The limits on the voltage, fed to the motor, are taken into account explicitly. The straight beam-and-ball system has one unstable mode in the motion near the equilibrium point. The proposed control law ensures that the basin of attraction coincides with the controllability domain. The circular beam-and-ball system has two unstable modes near the equilibrium point. Therefore, this device, never considered in the past, is much more difficult to control than the straight beam-and-ball system. The main contribution is to propose a simple new control law, which ensures by adjusting its gain parameters that the basin of attraction arbitrarily can approach the controllability domain for the linear case. For both nonlinear systems, simulation results are presented to illustrate the efficiency of the designed nonlinear control laws and to determine the basin of attraction

A method for the reconstruction of unknown non-monotonic growth functions in the chemostat

We propose an adaptive control law that allows one to identify unstable steady states of the open-loop system in the single-species chemostat model without the knowledge of the growth function. We then show how one can use this control law to trace out (reconstruct) the whole graph of the growth function. The process of tracing out the graph can be performed either continuously or step-wise. We present and compare both approaches. Even in the case of two species in competition, which is not directly accessible with our approach due to lack of controllability, feedback control improves identifiability of the non-dominant growth rate.Comment: expansion of ideas from proceedings paper (17 pages, 8 figures), proceedings paper is version v