bluuebunny/crossref_metadata_2025 huggingface dataset:
Lab-Scale Experimental Crosswind Flight Control System Prototyping for an Airborne Wind Energy System
Authors: Cobb Mitchell , Vermillion Christopher , Fathy Hosam
Published: February 2017

This paper presents an original experimental setup for controlling and measuring the crosswind flight of airborne wind energy systems in a laboratory environment. Execution of cross-wind flight patterns, which is achieved in this work through the asymmetric motion of three tethers, enables dramatic increases in energy generation compared with stationary operation. Achievement of crosswind flight in the 1:100-scale experimental framework described herein allows for rapid, inexpensive, and dynamically scalable characterization of new control algorithms without recourse to expensive full-scale prototyping. This work is the first example of successful lab-scale control and measurement of crosswind motion for an airborne wind energy system. Specifically, this paper presents the experimental setup, crosswind flight control strategy, and experimental results for a model of the Altaeros Buoyant Airborne Turbine (BAT). The results demonstrate that crosswind flight control can achieve nearly 50 percent more power production then stationary operation, while also demonstrating the potential of the experimental framework for further algorithm development.
Filtered Dynamic Inversion for Time Delay Systems
Authors: Ghasemi Amir H.
Published: February 2017

This paper addresses the problem of command following for linear, multi-input multi-output, time delay systems using filtered dynamic inversion. The dynamic inversion control input is obtained for linear time-delay systems utilizing the ring framework. This control input is combined with a low-pass-filter to construct a high-gain-stabilizing controller. It is shown that the time-delay-filtered-dynamic-inversion (TD-FDI) uses output feedback, reference-model-input feed-forward, and only requires limited model information. Numerical simulations demonstrate that for sufficiently large choice of a single control parameter, TD-FDI makes the L∞ of the command-following error arbitrarily small.
Development of an Emergency Lane Change System in Highway Driving
Authors: Coskun Serdar , Langari Reza
Published: February 2017

This paper presents an approach to the lane change safety system for collision avoidance. The solution is presented in two distinct steps. We first propose a decision strategy based on a discrete time Markov process to determine the safe lane utilizing a set of transition probabilities. These probabilities are calculated according to the distance of the subject vehicle from the surrounding vehicles. The output of decision process is fed to a controller formulated using an ℋ∞ scheme to move the vehicle to the desired lane. The overall strategy can be viewed as a combination of continuous control with a discrete decision process. The performance of the proposed scheme is compared with the so-called human-driver model (HDM) based control, which has been broadly discussed in the literature. The simulation study shows the superiority of the proposed controller in terms of trajectory tracking of the reference path, disturbance rejection of the wind load, and effective control input.
A Nonlinear Data-Driven Model of Glucose Dynamics Accounting for Physical Activity for Type 1 Diabetes: An In Silico Study
Authors: Xie Jinyu , Wang Qian
Published: February 2017

Physical activity is an important physiological information which should be taken into account by artificial pancreas to achieve optimal control of blood glucose in Type 1 Diabetes patients. An accurate glucose dynamic model with physical activity as an additional input is highly desirable for the next generation artificial pancreas. In this paper, we present a nonlinear data-driven model that captures both the insulin-independent and -dependent effect of physical activity, especially the prolonged effect of physical activity on insulin sensitivity that can last 24–48 hours post exercise. The model was identified and validated using data sets generated by a physiological glucose-exercise model under a clinical training protocol. Compared to modeling the effect of physical activity as a linear additive term only in a glucose dynamic equation, the proposed nonlinear model showed significant improvement of prediction accuracy in all three metrics, particularly in large prediction horizons (P < 0.05). Further investigation in time-series data indicates that the improvement mainly resulted from the better prediction of glucose around the first meal time after exercise (6 to 8 hours after the meal was taken).
Can Photovoltaic Battery Energy Storage Systems Be Self-Balancing?
Authors: Mishra Partha P. , Fathy Hosam K.
Published: February 2017

This paper proposes a novel approach for integrating battery storage into photovoltaic (PV) arrays. The approach relies on the integration of PV arrays with individual batteries to form “hybrid cells” that are then assembled into series strings. We use Lyapunov analysis to show that the proposed hybrid strings are globally asymptotically self-balancing, meaning that initial variations in state of charge (SOC), no matter how large, converge to zero. The PV subsystem serves as a negative feedback path that guarantees self-balancing without requiring dedicated balancing circuits. This significantly reduces the cost of the power electronics needed for integrating batteries into PV farms, compared to typical integration topologies. The paper uses local linearization to approximate the balancing rate, thereby highlighting its independence of battery pack length and elucidating its dependence on subsystem sizing. Finally, a simulation study validates the paper’s theoretical insights regarding self-balancing, and examines its sensitivity to parameter heterogeneities.
Generation of Probabilistically Optimal Paths for Nonholonomic Needle Insertion
Authors: Lin Jianping , Park Wooram
Published: February 2017

Rapidly-exploring Random Tree (RRT) is a sampling-based algorithm which is designed for path planning problems. It is efficient to handle high-dimensional configuration space (C-space) and nonholonomic constraints. Under the nonholonomic constraints, the RRT can generate paths between an initial state and a goal state while avoiding obstacles. Since this framework assumes that a system is deterministic, more improvement should be added when the method is applied to a system with uncertainty. In robotic systems with motion uncertainty, probability for successful targeting and obstacle avoidance are more suitable measurement than the deterministic distance between the robot system and the target position. In this paper, the probabilistic targeting error is defined as a root-mean-square (RMS) distance between the system to the desired target. The proximity of the obstacle to the system is also defined as an averaged distance of obstacles to the robotic system. Then, we consider a cost function that is a sum of the targeting error and the obstacle proximity. By numerically minimizing the cost, we can obtain the optimal path. In this paper, a method for efficient evaluation and minimization of this cost function is proposed and the proposed method is applied to nonholonomic flexible medical needles for performance tests.
A Model Predictive Control Law for a Vapor Compression Cycle System
Authors: Ngo Anhtuan D. , Cory Joshua R.
Published: February 2017

During the development of next generation tactical aircraft, thermal management is given significant consideration due to higher transient cooling demands, with stricter temperature limits along with the smaller size and weight in the cooling system hardware. Traditional control approaches, such as proportional-integral-derivative (PID), are sufficient to achieve the desired steady-state error performance for a thermal system with no constraints on the control inputs. The traditional control techniques may not be well-suited for thermal systems with constrained inputs. In this paper, we apply the Model Predictive Control (MPC) technique on an input-constrained thermal system and examine the system performance under a large transient thermal load and control input limits through the anticipation of the known thermal load. The results include design and implementation of an MPC controller for a high-fidelity, nonlinear vapor compression cycle model, as well as comparison of the MPC results to those of a finely tuned PID controller.
A Three Dimensional Model of Zebrafish Swimming
Authors: Mwaffo Violet , Butail Sachit , Porfiri Maurizio
Published: February 2017

Zebrafish is becoming an important animal model in pre-clinical studies for its genetic similarity to humans and ease of use in the laboratory. In recent years, animal experimentation has faced several ethical issues, calling for alternative methods that capitalize on dynamical systems theory. Here, we propose a computational modeling framework to simulate zebrafish swimming in three dimensions (3D) in the form of a coupled system of stochastic differential equations. The model is capable of reproducing the burst-and-coast swimming style of zebrafish, speed modulation, and avoidance of tank boundaries. Model parameters are calibrated on an experimental dataset of zebrafish swimming in 3D and validated by comparing established behavioral measures obtained from both synthetic and experimental data. We show that the model is capable of accurately predicting fish locomotion in terms of the swimming speed and number of entries in different sections of the tank. The proposed model lays the foundations for in-silico experiments of zebrafish neurobehavioral research.
Autonomous Charging for an Underwater Robotic Fish by Direct Contact
Authors: Phamduy Paul , Cheong Jayhwan , Porfiri Maurizio
Published: February 2017

The operation of autonomous underwater vehicles is often hindered by their battery capacity, limiting the duration of its use. Here, we propose an integrated solution for autonomous charging of a robotic fish via direct contact through a novel claw mechanism for docking guidance. To assist the robotic fish in the docking process, the system incorporates a charging station designed with form-fit claws. A controller is designed to monitor the battery level of the robotic fish during free swimming and coordinate the docking process with respect to the maneuvers of both the robot and form-fit claws. Upon recognizing a low battery level, the controller commands the robotic fish to begin the docking process, and video feedback from an overhead camera is used to inform the autonomous navigation toward the charging station. After reaching a battery level threshold, the robotic fish is then released back in the water and returns to free swimming until the battery is discharged again. Through a series of experiments, we demonstrate the possibility of prolonged operation, consisting of repeated cycles of autonomous charging. Our proposed charging method enables prolonged autonomous swimming with minimal human supervision, opening the door for new, transformative applications of robotic fish in laboratory research and field deployment.
Assessing Fuel Economy From Automated Driving: Influence of Preview and Velocity Constraints
Authors: Prakash Niket , Cimini Gionata , Stefanopoulou Anna G. , Brusstar Matthew J.
Published: February 2017

Constrained optimization control techniques with preview are designed in this paper to derive optimal velocity trajectories in longitudinal vehicle following mode, while ensuring that the gap from the lead vehicle is both safe and short enough to prevent cut-ins from other lanes. The lead vehicle associated with the Federal Test Procedures (FTP) [1] is used as an example of the achieved benefits with such controlled velocity trajectories of the following vehicle. Fuel Consumption (FC) is indirectly minimized by minimizing the accelerations and decelerations as the autonomous vehicle follows the hypothetical lead. Implementing the cost function in offline Dynamic Programming (DP) with full drive cycle preview showed up to a 17% increase in Fuel Economy (FE). Real time implementation with Model Predictive Control (MPC) showed improvements in FE, proportional to the prediction horizon. Specifically, 20s preview MPC was able to match the DP results. A minimum of 1.5s preview of the lead vehicle velocity with velocity tracking of the lead was required to obtain an increase in FE.

The optimal velocity trajectory found from these algorithms exceeded the presently allowable error from standard drive cycles for FC testing. However, the trajectory was still safe and acceptable from the perspective of traffic flow. Based on our results, regulators need to consider relaxing the constant velocity error margins around the standard velocity trajectories dictated by the FTP to encourage FE increase in autonomous driving.
A Reference Governor for Nonlinear Systems Based on Quadratic Programming
Authors: Li Nan I. , Kolmanovsky Ilya , Girard Anouck
Published: February 2017

The reference governor modifies set-point commands to a closed-loop system in order to enforce state and control constraints. In this paper, we describe an approach to reference governor implementation for nonlinear systems, which is based on bounding (covering) the response of a nonlinear system by the response of a linear model with a set-bounded disturbance input. Such a design strategy is of interest as it reduces the online optimization problem to a convex quadratic programming (QP) problem with linear inequality constraints, thereby permitting standard QP solvers to be used. A numerical example is reported.
Autonomous Collision Avoidance as a Markov Decision Process
Authors: Rastgoftar Hossein , Ni Xiangyu , Atkins Ella M.
Published: February 2017

In this paper, we apply a Markov Decision Process (MDP) to assure collision avoidance and specify optimal paths for evolution of an agent with nonlinear dynamics. We consider evolution of an autonomous wheeled robot in a motion field where a malicious agent has stochastic transitions over the field. By knowing the history of malicious agent transition as well as initial and goal destinations of the autonomous robot, the optimal path is obtained using the Bellman equation. We propose a novel finite time controller that assures reachability of desired way-points along the optimal path, where the optimal path is obtained without deriving the Hamiltonian.
MPC Based Automated Steering of a Low Speed Shuttle for Socially Acceptable Accident Avoidance
Authors: Wang Haoan , Cao Yue , Aksun Güvenç Bilin , Güvenç Levent
Published: February 2017

This paper presents a socially acceptable collision avoidance system for an automated vehicle based on the elastic band method. Both stationary and moving Vulnerable Road Users (VRUs: pedestrians or bicyclists) are considered in the proposed system. A collision free path is first determined and then Model Predictive Control (MPC) based vehicle front wheel steering is applied to track this collision free path. For the purposes of benchmarking and comparison, the results of a conventional PID steering controller are also presented. The designed system is tested with simulations on a path chosen from the west campus of the Ohio State University, whose waypoints are extracted automatically from OpenStreetMap (OSM). Simulation results show that the MPC based steering control system successfully achieves the required collision avoidance and path following and has comparable or better performance when compared with the conventional PID solution.
State of Charge Estimation for an Electric Wheelchair Using a Fuel Gauge Model
Authors: Miller Christopher , Wolkowicz Kelilah , Safi Jariullah , Brennan Sean N.
Published: February 2017

Electric wheelchair users depend on a reliable power system in order to regain mobility in their daily lives. If a wheelchair’s battery power depletes without the user being aware, the individual may become stranded, further limiting their freedom of mobility and potentially placing the user in a harmful situation. This research seeks to develop a State-of-Charge (SOC) estimator for the batteries of an electric wheelchair. A second-order equivalent circuit battery model is developed and parameterized for a wheelchair’s lead-acid battery pack. To simplify the SOC estimation, this algorithm models a vehicle’s fuel gauge. A coulomb accumulator is incorporated to estimate energy usage in the non-linear region of the OCV-SOC curve, while a Kalman filter is used to estimate SOC in the linear region of the curve. The estimator is verified using experimentally collected data on-board a robotic wheelchair. The implementation of these algorithms with powered wheelchairs can significantly improve the estimation of wheelchair battery power and can ultimately be coupled with warning systems to alert users of depleting battery life, as well as enable low-power modes to increase wheelchair user safety.
Level-Set Based Greedy Algorithm With Sequential Gaussian Process Regression for Implicit Surface Estimation
Authors: Yang Shiyi , Jeon Soo , Choi Jongeun
Published: February 2017

This paper proposes an efficient greedy algorithm to estimate the object shape within a limited number of sample data (i.e. the touch-down points). Specifically, we treat the object shape as an implicit surface which is defined as the zero level-set of an unknown function and apply Gaussian process to estimate the surface. The mutual information criteria is utilized to decide which point should be sampled in the next iteration. To expedite the estimation process, we implement sequential Gaussian process for computational efficiency and significantly reduce the computational cost by selecting search area based on the estimated level-set variance. We present some simulation results to compare the performance of the proposed algorithm with the random sampling algorithm and demonstrate the improvements in both speed and accuracy over the random sampling algorithm.
Visibility-Based Distributed Deployment of Robotic Teams in Polyhedral Terrains
Authors: Ma Aaron , Cortés Jorge
Published: February 2017

This paper presents deployment strategies for a team of multiple mobile robots with line-of-sight visibility in 1.5D and 2.5D terrain environments. Our objective is to distributively achieve full visibility of a polyhedral environment. In the 1.5D polyhedral terrain, we achieve this by determining a set of locations that the robots can distributively occupy. In the 2.5D polyhedral terrain, we achieve full visibility by simultaneously exploring, coloring, and guarding the environment.
Probabilistic Freeway Ramp Metering
Authors: Mehr Negar , Horowitz Roberto
Published: February 2017

Ramp metering is proved to be an effective strategy for reducing or avoiding freeway traffic congestion. As a result, huge amount of research has been conducted on synthesizing effective ramp metering controls. In the previous works, freeway is assumed to be a deterministic system which is in contrast with the intrinsic stochastic nature and behavior of freeways. Our work focuses on bridging this gap, and we propose a framework for freeway ramp metering in a probabilistic setting. Our algorithm finds onramp flows in a freeway network while treating exogenous vehicular arrivals as random variables with known distributions, allowing for the network arrivals to conform with their stochastic nature. We use sampling techniques in a model predictive control setup to formulate a tractable approximation of our stochastic optimization. Furthermore, we demonstrate how to relax the non-linear constraints of our optimization to create a linear program with an augmented set of constraints. We prove that the solution of our linear program formulation is the same as the solution of the original mixed-integer formulation. We showcase the results of our algorithm on an exemplar freeway network and introduce multiple interesting future research directions that are important and can be pursued solely in a stochastic framework.
Settling Control of the Triple-Stage Hard Disk Drives Using Robust Output Feedback Model Predictive Control
Authors: Nguyen Huy , Bagherieh Omid , Horowitz Roberto
Published: February 2017

Track settling control for a hard disk drive with three actuators has been considered. The objective is to settle the read/write head on a specific track by following the minimum jerk trajectory. Robust output feedback model predictive control methodology has been utilized for the control design which can satisfy actuator constraints in the presence of noises and disturbances in the system. The controller is designed based on a low order model of the system and has been applied to a higher order plant in order to consider the model mismatch at high frequencies. Since the settling control generally requires a relatively low frequency control input, simulation result shows that the head can be settled on the desired track with 10 percent of track pitch accuracy while satisfying actuator constraints.
Obstacle Filtering Algorithm for Control of an Autonomous Road Vehicle in Public Highway Traffic
Authors: Wang Qian , Ayalew Beshah
Published: February 2017

This paper presents an obstacle filtering algorithm that mimics human driver-like grouping of objects within a model predictive control scheme for an autonomous road vehicle. In the algorithm, a time to collision criteria is first used as risk assessment indicator to filter the potentially dangerous obstacle object vehicles in the proximity of the autonomously controlled vehicle. Then, the filtered object vehicles with overlapping elliptical collision areas put into groups. A hyper elliptical boundary is regenerated to define an extended collision area for the group. To minimize conservatism, the parameters for the tightest hyper ellipse are determined by solving an optimization problem. By excluding undesired local minimums for the planning problem, the grouping alleviates limitations that arise from the limited prediction horizons used in the model predictive control. The computational details of the proposed algorithm as well as its performance are illustrated using simulations of an autonomously controlled vehicle in public highway traffic scenarios involving multiple other vehicles.
A Two-Level Adaptive Fuzzy Control Algorithm for Beyond Pull-In Stabilization of Electrostatically Actuated Microplates
Authors: Radgolchin Moeen , Moeenfard Hamid , Ghasemi Amir H.
Published: February 2017

The objective of this paper is to present an adaptive multi-level fuzzy controller to stabilize the deflection of an electrostatically actuated microplate beyond its pull-in range. Using a single mode approximation along with utilizing the Lagrange equations, the dynamic behavior of the microplate is described in modal space by an ordinary differential equation. By different static and dynamic simulations, the system and the dependence of the deflection to the input applied voltage is identified linguistically. Then, based on the linguistic description of the system, a fuzzy controller is designed to stabilize the microplate at the desired deflections. To improve the performance specifications of the closed-loop system, another fuzzy controller at a higher level is designed to adjust the parameters of the main controller in real time. The simulation results reveal that by using the proposed single level and adaptive two level controllers, the control objective is met effectively with good performance specifications. It is also observed that adding a supervisory level to the main controller can reduce the overshoot and the settling time in beyond pull-in stabilization of electrostatically actuated microplates. The qualitative knowledge resulting from this research can be generalized and used for development of efficient controllers for N/MEMS actuators and electrostatically actuated nano/micro positioning systems.
Auto-Tuning Tub-Level Control of Blender in Hydraulic Fracturing
Authors: Chen Zheng , Cargill Leslie , Naizer Brent
Published: February 2017

Hydraulic fracturing is one of the key technologies for producing shale oil and gas. During hydraulic fracturing, a blender is used to mix sand with water and chemicals to obtain a fluidic mixture that will be pumped down a well to frack rocks. In order to achieve high-quality fracturing during a job, the blender needs to maintain its tub level as well as the density of the fluidic mixture. In this paper, an auto-tuning proportional-integral (PI) control is developed for the blender automation system to maintain the tub level of its fluidic mixture. The control system adopts a single-loop PI with gains that can be auto-tuned during a job. A relay feedback test is conducted for auto-tuning the PI gains online. The auto-tuning PI control has been successfully tested in a blender simulator. Experimental results have shown that the control performance was improved after auto-tuning and that the control system was adaptive to variation in system parameters.
Damage Detection of Bridge Network With Spatiotemporal Pattern Network
Authors: Liu Chao , Gong Yongqiang , Laflamme Simon , Phares Brent , Sarkar Soumik
Published: February 2017

The alarmingly degrading state of transportation infrastructures combined with their key societal and economic importance calls for automatic condition assessment methods to facilitate smart management of maintenance and repairs. In particular, scalable data-driven approaches is of great interest, because it can deal with large volume of streaming data without requiring models that can be inaccurate and computationally expensive to run. Properly designed, a data-driven methodology could enable fast and automatic evaluation of infrastructures, discovery of causal dependencies among various sub-system dynamic responses, and inference and decision making with uncertainties and lack of labeled data. In this work, a spatiotemporal pattern network (STPN) strategy built on symbolic dynamic filtering (SDF) is applied to explore spatiotemporal behaviors in bridge network. Data from strain gauges installed on two bridges are simulated by finite element method, and the causality among strain data in spatial and temporal resolutions is analyzed. Case studies are conducted for truck identification and damage detection from simulation data. Results show significant capabilities of the proposed approach in: (i) capturing spatiotemporal features to discover causality between bridges (geographically close), (ii) robustness to noise in data for feature extraction, and (iii) detecting and localizing damage via the comparison of behaviors within the bridge network.
Simultaneous Optimal Robot Base Placement and Motion Planning Using Expanded Lagrangian Homotopy
Authors: Dharmawan Audelia Gumarus , Foong Shaohui , Soh Gim Song
Published: February 2017

This paper presents a new approach to simultaneously determine the optimal robot base placement and motion plan for a prescribed set of tasks using expanded Lagrangian homotopy. First, the optimal base placement is formulated as a constrained optimization problem based on manipulability and kinematics of the robot. Then, the constrained optimization problem is expressed into the expanded Lagrangian system and subsequently converted into a homotopy map. Finally, the Newton-Raphson method is used to solve the constrained optimization problem as a continuation problem. The complete formulation for the case of a 6-DOF manipulator is presented and a planar optimal mobile platform motion planning approach is proposed. Numerical simulations confirm that the proposed approach is able to achieve the desired results. The approach also shows the potential for incorporating factors such as joint limits or collision avoidance into the motion planning process as inequality constraints and will be part of future research.
Effect of Moisture on the Efficiency and Power Density of a Liquid Piston Air Compressor/Expander
Authors: Srivatsa Anirudh , Li Perry Y.
Published: February 2017

For a compressed air energy storage (CAES) system to be competitive for the electrical grid, the air compressor/expander must be capable of high pressure, efficient and power dense. However, there is a trade-off between efficiency and power density mediated by heat transfer, such that as the process time increases, efficiency increases at the expense of decreasing power. This trade-off can be mitigated in a liquid (water) piston air-compressor/expander with enhanced heat transfer. However, in the past, dry air has been assumed in the design and analysis of the compression/expansion process. This paper investigates the effect of moisture on the compression efficiency and power. Evaporation and condensation of water play contradictory roles — while evaporation absorbs latent heat enhancing cooling, the tiny water droplets that form as water condenses also increase the apparent heat capacity. To investigate the effect of moisture, a 0-D numerical model that takes into account the water evaporation/condensation and water droplets have been developed. Results show that inclusion of moisture improves the efficiency-power trade-off minimally at lower flow rates, high efficiency cases, and more significantly at higher flow rates, lower efficiency cases. The improvement is primarily attributed to the increase in apparent heat capacity due to the increased propensity of water to evaporate.
A Robotic Knee Orthosis for Sit-to-Stand Assistance
Authors: Thapa Saroj , Zheng Hao , Kogler Geza F. , Shen Xiangrong
Published: February 2017

Nowadays a large number of individuals suffer from lower-limb weaknesses caused by multiple reasons, such as the gradual degeneration of musculoskeletal structure in elderly population, and the pathological losses of neuromuscular functions in stroke and spinal cord injury patients. In this paper, the design and control of a new robotic knee orthosis is presented, with the objective of assisting the user’s locomotion (primarily sit-to-stand motion) by applying an assistive torque on the knee, the largest joint in the human body. The orthosis consists of an orthosis shell and an actuation unit. The former functions as the user interface that transfers the assistive torque to the human body, while the latter generates the desired assistive torque with a motor-ball screw assembly. Through detailed design calculation, it has been demonstrated that the actuated orthotic joint is able to provide 20% of the required knee torque in the sit-to-stand motion. A controller for the robotic orthosis has also been developed by studying and emulating the knee biomechanics in the sit-to-stand motion. Benchtop testing conducted on a surrogate limb system demonstrated that the joint motion powered by the robotic orthosis is stable, smooth, and similar to the biological knee motion in the human sit-to-stand motion.
Disturbance and Performance-Weighted Iterative Learning Control With Application to Modulated Tool Path-Based Manufacturing
Authors: DiMarco Christopher , Vermillion Christopher , Ziegert John C.
Published: February 2017

Single-point metal turning processes can create chip nests that are hazards to both parts and machine tools. This is mitigated by a process called Modulated Tool Path (MTP) machining, which superimposes an oscillation in the tool tip feed direction in order to break these chips and provide an adequate surface finish. MTP machining is highly sensitive to the amplitude and frequency of this oscillation, both of which can often be diminished by standard machine tool controllers. These controllers are also unresponsive to iteration-varying disturbances such as temperature fluctuations, which can cause positional and velocity-related inaccuracies. This paper presents a library-based variant of Iterative Learning Control (ILC) called Disturbance and Performance-Weighted ILC (DPW-ILC), which is designed to improve the accuracy of machine tool trajectories that are highly oscillatory in nature, as well as provide robustness to varying, but measurable disturbances. DPW-ILC has been shown in simulation to provide a tremendous accuracy benefit over standard ILC techniques, specifically in the presence of two separate types of temperature-based disturbances.
Computationally Efficient Dynamics Modeling for Downhole Drilling System Integrating Finite Element and Transfer Matrix
Authors: Ke Chong , Song Xingyong
Published: February 2017

This paper proposes a novel computationally efficient dynamics modeling approach for downhole well drilling system. The existing drilling modeling methods are either computationally intensive such as those using finite element method (FEM), or weak in fidelity for complex geometry such as those using transfer matrix method (TMM). To take advantage of the benefits of FEM and TMM and avoid their drawbacks, this paper presents a new hybrid method integrating both of the aforementioned modeling approaches, enabled by the unique structural geometry of the drilling system. Numerical simulation results are presented to demonstrate the effectiveness of the proposed hybrid modeling approach.
Design of a Control System for Serial Mechanisms
Authors: Zhang Dan , Wei Bin
Published: February 2017

A hybrid control system for multi degrees of freedom robotic manipulator is designed by integrating a proportional-integral-derivative controller (PID) and a model reference adaptive controller (MRAC) in order to further improve the accuracy and joint convergence speed performance. For the 1-DOF link, because the inertia matrices and nonlinear term of the dynamic equation are constant, we can directly combine the PID and MRAC controller to design the PID+MRAC controller. However, for the more than 1-DOF link case, it is no longer applicable because the inertia matrices and nonlinear term of the dynamic equation are not constant. By using an improved adaptive algorithm and structure, and by combining the PID and improved MRAC controllers, a controller is designed for the more than 1-DOF link case. The convergence performance of the PID controller, MRAC and the PID+MRAC hybrid controller for 1-DOF, 2-DOF and subsequently 3-DOF manipulators are compared.
Bio-Inspired Robotic Fish Propelled by Multiple Artificial Fins
Authors: Hou Piqi , Ye Zhihang , Chen Zheng
Published: February 2017

With advances in actuation and sensing, smart materials has drawn a growing attention from researchers in under water robotic fish. In this paper, a compact, noiseless, and untethered biomimetic robotic fish propelled by Ionic Polymer-Metal Composite (IPMC) actuators is developed. The robot fish employs two pectoral fins to generate steering and one caudal fin to generate main propulsion. A passive plastic fin is attached to the IPMC beam to enhance propulsion. With multiple IPMC fins, the fish is capable of 2D maneuvering. One small size programmable circuit board is designed for the 2D controllable fish. The Experimental results have shown that the forward-swimming speed can reach up to 1cm/sec and the both left-turning and right turning speed can reach up to 2 rad/sec.
Hybrid Low Pass and De-Trending Filter for Robust Position Estimation of Quadcopters
Authors: Mishra Shatadal , Zhang Wenlong
Published: February 2017

In this paper, a hybrid low-pass and de-trending (HLPD) filtering technique is proposed to achieve robust position estimates using an optical flow based sensor which calculates velocity information at a rate of 400 Hz. In order to filter out the high-frequency oscillation in the velocity information, a standard low-pass filter is implemented. The low-pass filter successfully eliminates sudden jumps and missing data-points, which prevents unprecedented maneuvers and mid-air crashes. The integrated position estimate has the accumulated drift which occurs due to electrical signal and temperature fluctuations together with other environmental factors which affect the data acquisition from the optical flow sensor. A recursive linear least squares fit is performed for the drift model and de-trending is applied to the integrated position signal. The performance of the proposed estimator is validated by comparing with model-identification based weighted average (MI-WA) position estimator, which is commonly used in quadcopters for position estimation. Simulation and experimental flight tests are conducted and the results show that the flight performance of HLPD filter is better than the extensively used MI-WA position filter in hover and square pattern flight tests.
Design, Fabrication and Control of a Tilt Rotor Quadcopter
Authors: Nemati Alireza , Soni Neal , Sarim Mohammad , Kumar Manish
Published: February 2017

The aim of the present work is to design, fabricate, control and experimentally study quadcopters with tilting propellers. Conventional quadcopters, due to limitation in mobility, belong to a class of under-actuated robots which cannot achieve any arbitrary desired state or configuration. The tilting rotor quadcopter provides the added advantage in terms of additional stable configurations that are made possible by additional actuated controls that convert the conventional quadcopter to a fully actuated robot. The tilting rotor quadcopter design is accomplished by using an additional motor for each rotor that enables the rotor to rotate along the axis of the quadcopter arm.

The dynamic model and the controller that have been proposed and reported by the authors of this paper in the previous publications were verified with the help of numerical studies for different flight scenarios. Subsequently, two different models of the vehicle were designed, fabricated and experimentally tested for different flight plans.
The Encyclopedic Impulse in Religious Studies
Authors: Ziolkowski Eric
Published: February 2017

It is no mere coincidence that the ongoing revolution in information technology has coincided with an explosive increase of reference works, not the least in religious studies and biblical studies. The unprecedented production rate of such works today led one scholar to dub our times “a golden age of reference books,” resulting in the challenge of “oversupply.” This article reflects historically upon the basic impulse behind the conceptualizing, planning, and production of large encyclopedias in religious and biblical studies: the sense of information overload, and the desire to bring order to it.
The Encyclopedia of Religion in a Digital Age: Entries Not Found, Treasures Not Mined
Authors: Jones Lindsay
Published: February 2017

The wealth of online materials concerning religion may seem to supplant and imperil the stature of Mircea Eliade's 16-volume Encyclopedia of Religion (1987), long considered the standard reference work in the field. This article argues, however, that the seminal encyclopedia, especially in its heavily revised and expanded second edition (2005), continues to provide researchers of religion a uniquely valuable resource—but only when they are awakened to the theoretical and explicitly comparative configuration of the set. To that end, the discussion enumerates some of the encyclopedia's most distinctive features that are not matched in other reference works, digital or print.
Effects of ceiling phase gradients on the acoustic environment on roadside balconies
Authors: Wang Xu , Yu Wuzhou , Zhu Xingyi , Jiang Zaixiu , Mao Dongxing
Published: February 2017

The screening effect of a roadside balcony deteriorates considerably due to sound reflection from its ceiling. Nonetheless, this drawback can be eliminated by artificially steering the reflected sound away from the building facade, which is achieved by introducing impedance inhomogeneity to the ceiling surface. This paper presents an elaborated investigation on the effect of the phase gradient of a ceiling surface on screening exterior noise, theoretically and numerically. By balancing its sound-steering capability and performance fluctuation level, such a balcony ceiling may have the potential to be widely used on roadside buildings.
Fasting-mimicking diet and markers/risk factors for aging, diabetes, cancer, and cardiovascular disease
Authors: Wei Min , Brandhorst Sebastian , Shelehchi Mahshid , Mirzaei Hamed , Cheng Chia Wei , Budniak Julia , Groshen Susan , Mack Wendy J. , Guen Esra , Di Biase Stefano , Cohen Pinchas , Morgan Todd E. , Dorff Tanya , Hong Kurt , Michalsen Andreas , Laviano Alessandro , Longo Valter D.
Published: February 2017

A periodic fasting diet improves markers of metabolic dysfunction, particularly in people already at risk.
Transcription Profiling ofBacillus subtilisCells Infected with AR9, a Giant Phage Encoding Two Multisubunit RNA Polymerases
Authors: Lavysh Daria , Sokolova Maria , Slashcheva Marina , Förstner Konrad U. , Severinov Konstantin
Published: February 2017

Bacteriophage AR9 is a recently sequenced jumbo phage that encodes two multisubunit RNA polymerases. Here we investigated the AR9 transcription strategy and the effect of AR9 infection on the transcription of its host,Bacillus subtilis. Analysis of whole-genome transcription revealed early, late, and continuously expressed AR9 genes. Alignment of sequences upstream of the 5′ ends of AR9 transcripts revealed consensus sequences that define early and late phage promoters. Continuously expressed AR9 genes have both early and late promoters in front of them. Early AR9 transcription is independent of protein synthesis and must be determined by virion RNA polymerase injected together with viral DNA. During infection, the overall amount of host mRNAs is significantly decreased. Analysis of relative amounts of host transcripts revealed notable differences in the levels of some mRNAs. The physiological significance of up- or downregulation of host genes for AR9 phage infection remains to be established. AR9 infection is significantly affected by rifampin, an inhibitor of host RNA polymerase transcription. The effect is likely caused by the antibiotic-induced killing of host cells, while phage genome transcription is solely performed by viral RNA polymerases.

IMPORTANCEPhages regulate the timing of the expression of their own genes to coordinate processes in the infected cell and maximize the release of viral progeny. Phages also alter the levels of host transcripts. Here we present the results of a temporal analysis of the host and viral transcriptomes ofBacillus subtilisinfected with a giant phage, AR9. We identify viral promoters recognized by two virus-encoded RNA polymerases that are a unique feature of the phiKZ-related group of phages to which AR9 belongs. Our results set the stage for future analyses of highly unusual RNA polymerases encoded by AR9 and other phiKZ-related phages.
Genetic Predisposition To Acquire a Polybasic Cleavage Site for Highly Pathogenic Avian Influenza Virus Hemagglutinin
Authors: Nao Naganori , Yamagishi Junya , Miyamoto Hiroko , Igarashi Manabu , Manzoor Rashid , Ohnuma Aiko , Tsuda Yoshimi , Furuyama Wakako , Shigeno Asako , Kajihara Masahiro , Kishida Noriko , Yoshida Reiko , Takada Ayato
Published: February 2017

Highly pathogenic avian influenza viruses with H5 and H7 hemagglutinin (HA) subtypes evolve from low-pathogenic precursors through the acquisition of multiple basic amino acid residues at the HA cleavage site. Although this mechanism has been observed to occur naturally only in these HA subtypes, little is known about the genetic basis for the acquisition of the polybasic HA cleavage site. Here we show that consecutive adenine residues and a stem-loop structure, which are frequently found in the viral RNA region encoding amino acids around the cleavage site of low-pathogenic H5 and H7 viruses isolated from waterfowl reservoirs, are important for nucleotide insertions into this RNA region. A reporter assay to detect nontemplated nucleotide insertions and deep-sequencing analysis of viral RNAs revealed that an increased number of adenine residues and enlarged stem-loop structure in the RNA region accelerated the multiple adenine and/or guanine insertions required to create codons for basic amino acids. Interestingly, nucleotide insertions associated with the HA cleavage site motif were not observed principally in the viral RNA of other subtypes tested (H1, H2, H3, and H4). Our findings suggest that the RNA editing-like activity is the key mechanism for nucleotide insertions, providing a clue as to why the acquisition of the polybasic HA cleavage site is restricted to the particular HA subtypes.

IMPORTANCE
Influenza A viruses are divided into subtypes based on the antigenicity of the viral surface glycoproteins hemagglutinin (HA) and neuraminidase. Of the 16 HA subtypes (H1 to -16) maintained in waterfowl reservoirs of influenza A viruses, H5 and H7 viruses often become highly pathogenic through the acquisition of multiple basic amino acid residues at the HA cleavage site. Although this mechanism has been known since the 1980s, the genetic basis for nucleotide insertions has remained unclear. This study shows the potential role of the viral RNA secondary structure for nucleotide insertions and demonstrates a key mechanism explaining why the acquisition of the polybasic HA cleavage site is restricted to particular HA subtypes in nature. Our findings will contribute to better understanding of the ecology of influenza A viruses and will also be useful for the development of genetically modified vaccines against H5 and H7 influenza A viruses with increased stability.
Migrated Hem-o-Lok clips in the ureter: a rare cause of recurrent urinary tract infection
Authors: Shrivastava Prashant , Nayak Brusabhanu , Singh Prabhjot
Published: February 2017

Erosion of surgical materials into the adjacent organs following surgical procedures is a rare complication. Migrations of these surgical materials into the urinary tract like pelvicalyceal system, ureter and bladder have been reported following various urological procedures. We present a case of migrated Hem-o-Lok clips into the ureter following a laparoscopic partial nephrectomy for angiomyolipoma of the left kidney presented with recurrent urinary tract infection. The case was managed with ureteroscopic removal of clips. The patient is asymptomatic on last follow-up.
What is the relationship between age and deprivation in influencing emergency hospital admissions? A model using data from a defined, comprehensive, all-age cohort in East Devon, UK
Authors: Pereira Gray Denis , Henley William , Chenore Todd , Sidaway-Lee Kate , Evans Philip
Published: February 2017

Objectives

To clarify the relationship between social deprivation and age as two factors associated with emergency admissions to hospital.

Design

Emergency admissions for 12 months were analysed for patients in the NHS NEW Devon CCG. Social deprivation was measured by the Index of Multiple Deprivation (IMD). Logistic regression models estimated the separate and combined effects of social deprivation and age on the risk of emergency admissions for people aged under and over 65.

Setting

East Devon, UK—area of the NEW Devon CCG.

Population

765 861 patients in the CCG database.

Main outcome measure

Emergency admission to any English hospital.

Results

Age (p<0.001) and social deprivation (p<0.001) were significantly associated with emergency admission to hospital, but there was a significant interaction between age and social deprivation (p<0.001). From the third quintile of age upwards, age progressively overtakes deprivation and age has a dominant effect on emergency admissions over the age of 65. The effect of age was J-shaped in all deprivation groups, increasing exponentially after age 40. For patients under 65, age and social deprivation had similar risks for emergency admissions, the differences in risk between the top and bottom quintiles of IMD and age being ∼1.5 and 0.9 percentage points. In patients over 65, age had a much greater effect on the risk of admissions than social deprivation, the differences in risk between the top and bottom quintiles of IMD and age being ∼2.8 and 18.7 percentage points.

Conclusions

Risk curves for all social groups have similar shapes, implying a common biological pattern for ageing in any social group. Over age 65, the biological effects of ageing outweigh the social effects of deprivation. Our model enables CCGs to anticipate and plan for emergency admissions to hospital. These findings provide a new logic for allocating resources to different populations.