bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optimal Strategy for Multiple Evaders Against an Agile Pursuer
Authors: Liu Chunsheng , Trevorrow Mark V. 
Published: November 2019

Abstract
This paper focuses on the problem of multiple slow moving and less maneuverable evaders against an agile pursuer, addressing the optimal strategy for multiple evaders. This is the so-called wolf-sheep game. Two scenarios are examined: 1) both pursuer and evaders have perfect knowledge about opponents, and 2) the pursuer has limited detection capability. Since the wolf-sheep game involves the Boolean value state, the game is hard to solve using traditional methods. This paper adopts a hierarchical approach. The two player game is solved first. Then the solution of the multiplayer game is based on the two-player game and the pursuer chasing order. The optimal strategy is calculated based on Nash equilibrium. The game with limited detection capability is solved by maximizing the Close Point of Approach (CPA). The optimal solution will be found theoretically and numerically.
Kinetic to Potential Energy Transformation Using an Elastica
Authors: Chau Sheryl , Mukherjee Ranjan 
Published: November 2019

Abstract
The kinetic energy of a mass traveling in the horizontal direction can be fully transformed into potential energy using an elastica as a temporary storage element. This problem, which resembles the sport of pole-vaulting, is investigated using a non-dimensional framework and by solving the ensuing two-point boundary problem. Dimensional studies are conducted with the objective of better understanding the role of the mass of the vaulter, modeled here as the mass attached to the elastica, and torque applied by the vaulter, modeled here as external torque on the elastica, on vaulting performance. Simulation results indicate better vaulting performance, as indicated by higher non-dimensional potential energy, for lower mass and higher torque.
Evaluating the Performance of Foot Control of a Supernumerary Robotic Limb
Authors: Dougherty Zachary , Winck Ryder C. 
Published: November 2019

Abstract
Supernumerary robotic limbs may one day allow people to perform tasks as if they had an extra limb, extending human capabilities. One challenge with supernumerary robotic limbs is how to control them. One method is teleoperation using the foot. This allows a person to continue using their arms. However, it is not clearly known how well a person can physically and cognitively use a foot-controlled supernumerary robotic arm and both of their arms simultaneously. We present an experiment that shows that using the foot to control a supernumerary robotic arm improves task performance. The task was selected so that it could be performed using only two hands, where the hands switch between subtasks. The use of only two hands provides a baseline for comparison. The results show that using the foot with the hands improved performance relative to just using the hands alone.
Comparison of Adaptive Control Laws for Wind Rejection in Quadrotor UAVs
Authors: Verberne Johannes , Moncayo Hever 
Published: November 2019

Abstract
This paper presents the evaluation of adaptive control augmentation algorithms for wind disturbance rejection in small rotorcraft UAVs. The following control algorithms are developed in an effort to mitigate wind effects: baseline nonlinear dynamic inversion (NLDI), NLDI augmented with adaptive artificial neural networks (ANN), and NLDI augmented with ℒ1 output-feedback adaptive control. A six degrees-of-freedom nonlinear simulation environment is developed to evaluate the performance under different wind disturbance conditions. Monte Carlo analysis and a set of metrics are applied to compare and assess the overall performance of the developed control algorithms within a predefined wind envelope. These metrics provide a performance evaluation for trajectory tracking, angular rates tracking, attitude angle tracking and total energy consumption. The individual metrics are combined to provide the global performance index for the quadrotor with the developed control algorithms. Outdoor flight test results are included in this paper and the capabilities of these controllers to reduce wind disturbance effects on different flight tracking parameters are analyzed. The performance of the developed control laws is evaluated under nominal, low, medium and high wind disturbance conditions.
Control-Oriented Modeling and Repetitive Control in In-Layer and Cross-Layer Thermal Interactions in Selective Laser Sintering
Authors: Wang Dan , Jiang Tianyu , Chen Xu 
Published: November 2019

Abstract
Publisher’s Note:
This paper was selected for publication in ASME Letters in Dynamic Systems and Control.
https://www.asmedigitalcollection.asme.org/lettersdynsys/article/doi/10.1115/1.4046367/1074566/Control-Oriented-Modeling-and-Repetitive-Control
A Series Elastic Actuator Design and Control in a Linkage Based Hand Exoskeleton
Authors: Chauhan Raghuraj J. , Ben-Tzvi Pinhas 
Published: November 2019

Abstract
This paper presents the design of a series elastic actuator and a higher level controller for said actuator to assist the motion of a user’s hand in a linkage based hand exoskeleton. While recent trends in the development of exoskeleton gloves has been to exploit the advantages of soft actuators, their size and power requirements limit their adoption. On the other hand, a series elastic actuator can provide compliant assistance to the wearer while remaining compact and lightweight. Furthermore, the linkage based mechanism integrated with the SEA offers repeatability and accuracy to the hand exoskeleton. By measuring the user’s motion intention through compression of the elastic elements in the actuator, a virtual dynamic system can be utilized that assists the users in performing the desired motion while ensuring the motion stability of the overall system. This work describes the detailed design of the actuator followed by performance tests using a simple PD controller on the integrated robotic exoskeleton prototype. The performance of the proposed high level controller is tested using the integrated exoskeleton glove mechanism for a single finger, using two types of input motion. Preliminary results are discussed as well as plans for integrating the proposed actuator and high level controller into a complete hand exoskeleton prototype to perform intelligent grasping.
Self-Resonant Energy Harvester With a Passively Tuned Sliding Mass
Authors: Kim Hongjip , Smith Arthur , Barry Oumar , Zuo Lei 
Published: November 2019

Abstract
Passive tuning phenomenon with a sliding mass on a vibrating beam has been observed and studied in the literature. Such a phenomenon can be extended to self-resonant energy harvesting, where the natural frequency can be favorably adjusted to the excitation frequency for enhanced energy harvesting. In this paper, we consider the nonlinear dynamic coupling of a piezoelectric clamped-clamped beam with sliding mass and study experimentally and numerically how these nonlinear interactions affect the performance of the energy harvester. We derive the mathematical model using the extended Hamilton principle. The governing equations of motion are obtained as three coupled nonlinear partial differential equations. The Galerkin method is employed to obtain a reduced order model. Our mathematical formulation is validated via experiments and the results show very good agreement between the simulation and the experiment. Parametric studies are carried out to examine how key parameters affect the performance of the energy harvester. The findings suggest that a passively tuned mechanism with a small sliding mass can increase the power output even when the excitation frequency is far off the original resonance.
Optimal Maintenance of Electric Vehicle Battery System Through Overnight Home Charging
Authors: Jangra Sidharth , Chung Chien Hsin , Lai Qingzhi , Lin Xinfan 
Published: November 2019

Abstract
Plug-in electric vehicle (PEV) is emerging as one of the most viable choices for the transportation sector to reduce fossil fuel consumption and CO2 emission. As the most critical component of PEV, battery systems require intensive management and diagnostics to ensure safety, efficiency, and endurance. Most existing studies focus on battery management when PEVs are under operation while none has explored battery maintenance during overnight parking, which accounts for a majority of the time (&gt; 12 hours per day). Battery states during this period significantly affect the lifetime due to the side reactions that occur even when the battery is not in use. The process occurs at an accelerated rate when the battery energy level or temperature is too high or too low. In this paper, we propose to utilize an existing infrastructure available to PEV owners, the home charging unit, for intelligent battery maintenance during overnight parking. We will design an optimal charging profile that would charge the battery to a specific level while maintaining its states at optimal conditions to minimize degradation due to side reactions over the whole overnight period. Optimal charging profiles are created for different ambient temperatures and at different stages of battery life to investigate various scenarios. To demonstrate the effectiveness of the designed optimal charging profiles, the total capacity loss overnight is compared with those of three standard charging profiles.
A New Quasi-Steady In-Ground Effect Model for Rotorcraft Unmanned Aerial Vehicles
Authors: He Xiang , Leang Kam K. 
Published: November 2019

Abstract
This paper introduces a new quasi-steady in-ground effect model for rotorcraft unmanned aerial vehicles to predict the aerodynamic behavior when the vehicle’s rotors approach ground plane. The model assumes that the compression of the outflow due to the presence of ground plane induces a change in the induced velocity that can drastically affect the thrust and power output. The new empirical model describes the change in thrust as a function of the distance to an obstacle for a rotor in hover condition. Using blade element theory and the method of image, the model parameters are described in terms of the rotor pitch angle and solidity. Experiments with off-the-shelf, fixed-pitch propellers and 3D-printed variable pitch propellers are carried out to validate the model. Experimental results suggest good agreement with 9.5% root-mean-square error (RMSE) and 97% p-value of statistic significance.
Backstepping-Based Trajectory Tracking for Underwater Gliders
Authors: Coleman Demetris , Castaño Maria , Ennasr Osama , Tan Xiaobo 
Published: November 2019

Abstract
Autonomous underwater gliders have become valuable tools for a myriad of applications ranging from ocean exploration to fish tracking to environmental sampling. To be suitable for these types of applications, precise sensing and monitoring is desired, which makes accurate trajectory control important. However, highly nonlinear under-actuated dynamics present significant challenges in control of gliders. In this work a backstepping-based controller is proposed for an underwater glider to track a desired position and heading reference in the sagittal plane with only two control inputs, the buoyancy and center of gravity along the longitudinal direction. In particular,the under-actuation issue is addressed by exploiting the coupled dynamics and introducing a new modified error that combines the tracking errors of heading and position references. In addition, an auxiliary system is incorporated to account for input constraints. Finally, a sliding mode observer is designed to obtain the estimates of body-fixed velocities, to facilitate practical implementation of the designed controller. The effectiveness of the proposed control scheme is demonstrated via simulations and its advantages are shown via comparison with a PID controller.
Toward Magneto-Electroactive Endoluminal Soft (MEESo) Robots
Authors: Steiner Jake A. , Hussain Omar A. , Pham Lan N. , Abbott Jake J. , Leang Kam K. 
Published: November 2019

Abstract
This paper introduces a magneto-electroactive endoluminal soft (MEESo) robot concept, which could enable new classes of catheters, tethered capsule endoscopes, and other mesoscale soft robots designed to navigate the natural lumens of the human body for a variety of medical applications. The MEESo locomotion mechanism combines magnetic propulsion with body deformation created by an ionic polymer-metal composite (IPMC) electroactive polymer. A detailed explanation of the MEESo concept is provided, including experimentally validated models and simulated magneto-electroactive actuation results demonstrating the locomotive benefits of incorporating an IPMC compared to magnetic actuation alone.
Adaptive Control of Large-Scale Soft Robot Manipulators With Unknown Payloads
Authors: Terry Jonathan S. , Whitaker Justin , Beard Randal W. , Killpack Marc D. 
Published: November 2019

Abstract
The compliance and other nonlinear dynamics of large-scale soft robots makes effective control difficult. This is especially true when working with unknown payloads or when the system dynamics change over time which is likely to happen for soft robots. In this paper, we present a novel method of coupling model reference adaptive control (MRAC) with model predictive control (MPC) for platforms with antagonistic pneumatic actuators. We demonstrate its utility on a fully inflatable, six degree-of-freedom pneumatically actuated soft robot manipulator that is over two meters long. Specifically, we compare control performance with no integral controller, with an integral controller, and with MRAC when running a nominal model predictive controller with significant weight attached to the end effector.
A Stabilizing Control Algorithm for Asynchronous Parallel Quadratic Programming via Dual Decomposition
Authors: Lee Kooktae 
Published: November 2019

Abstract
Publisher’s Note:
This paper was selected for publication in ASME Letters in Dynamic Systems and Control.
https://www.asmedigitalcollection.asme.org/lettersdynsys/article/doi/10.1115/1.4046365/1074564/A-Stabilizing-Control-Algorithm-for-Asynchronous
Contagion Processes Over Temporal Networks With Time-Varying Backbones
Authors: Nadini Matthieu , Rizzo Alessandro , Porfiri Maurizio 
Published: November 2019

Abstract
Predicting the diffusion of real-world contagion processes requires a simplified description of human-to-human interactions. Temporal networks offer a powerful means to develop such a mathematically-transparent description. Through temporal networks, one may analytically study the co-evolution of the contagion process and the network topology, as well as incorporate realistic feedback-loop mechanisms related to individual behavioral changes to the contagion. Despite considerable progress, the state-of-the-art does not allow for studying general time-varying networks, where links between individuals dynamically switch to reflect the complexity of social behavior. Here, we tackle this problem by considering a temporal network, in which reducible, associated with node-specific properties, and irreducible links, describing dyadic social ties, simultaneously vary over time. We develop a general mean field theory for the Susceptible-Infected-Susceptible model and conduct an extensive numerical campaign to elucidate the role of network parameters on the average degree of the temporal network and the epidemic threshold. Specifically, we describe how the interplay between reducible and irreducible links influences the disease dynamics, offering insights towards the analysis of complex dynamical networks across science and engineering.
Voltage Response of Parametric Resonance of MEMS Circular Plates Under Hard Excitations
Authors: Beatriz Julio S. , Caruntu Dumitru I. 
Published: November 2019

Abstract
This work deals with the voltage response of parametric resonance of electrostatically actuated microelectromechanical (MEMS) circular plates under hard excitations. Method of Multiple Scales (MMS) and Reduced Order Model (ROM) method using two modes of vibration are used to predict the voltage-amplitude response of the MEMS circular plates. ROM is solved using AUTO 07p, a software package for continuation and bifurcation. MMS used in this paper has one term in the electrostatic force being considered significant. This is the way MMS is used to model hard excitations. MMS shows results similar to those of ROM at lower amplitudes and lower voltages. The differences between the two methods, MMS and ROM, are significant in high amplitudes for all voltages, and the differences are significant in all amplitudes for larger voltages. Significant differences can be noted in the effect of different parameters such as the detuning frequency and damping on the voltage response. ROM AUTO 07p is calibrated using ROM time responses in which the ROM is solved using the solver ode15s in Matlab.
Fused Model Predictive Control Techniques for Strategic Platooning Amongst Heterogeneous Pairs of Heavy-Duty Trucks
Authors: Earnhardt Christian , Groelke Ben , Borek John , Vermillion Chris 
Published: November 2019

Abstract
With pairs or groups of heterogeneous vehicles (with different masses, aerodynamic coefficients, etc.), collaborative platooning can be advantageous in some scenarios due to aerodynamic drag reduction, while being detrimental in other scenarios due to mismatches in vehicle properties. This paper introduces two controllers capable of alternating between independent vehicle velocity trajectory optimization (VTO) and a collaborative platooning/VTO approach based on the aggregate fuel savings of all vehicles within the platoon. The first uses the difference in mass between the vehicles within a platoon and the upcoming road grade to decide whether platooning will be economically advantageous, relying on a support vector classification algorithm to make the switching decision. The second runs both independent VTO and collaborative VTO/platooning in parallel, making a decision based on which method predicts the least amount of fuel consumption over an upcoming stretch of highway. The performance of these techniques was evaluated using a medium-fidelity Simulink model of a heavy-duty truck. Results show a 5.1% to 14.1% decrease in fuel consumption for the following vehicle of a platoon as compared to a baseline controller not platooning, where the exact fuel consumption improvement depends on the desired following distance. These results were also compared to a baseline that platooned over the entire route, providing evidence that there are situations where disengaging from a platoon is beneficial in the presence of heterogeneity.
Deep Reinforcement Learning for Adaptive Traffic Signal Control
Authors: Tan Kai Liang , Poddar Subhadipto , Sarkar Soumik , Sharma Anuj 
Published: November 2019

Abstract
Many existing traffic signal controllers are either simple adaptive controllers based on sensors placed around traffic intersections, or optimized by traffic engineers on a fixed schedule. Optimizing traffic controllers is time consuming and usually require experienced traffic engineers. Recent research has demonstrated the potential of using deep reinforcement learning (DRL) in this context. However, most of the studies do not consider realistic settings that could seamlessly transition into deployment. In this paper, we propose a DRL-based adaptive traffic signal control framework that explicitly considers realistic traffic scenarios, sensors, and physical constraints. In this framework, we also propose a novel reward function that shows significantly improved traffic performance compared to the typical baseline pre-timed and fully-actuated traffic signals controllers. The framework is implemented and validated on a simulation platform emulating real-life traffic scenarios and sensor data streams.
Delay-Dependent Output-Feedback Control for Blood Pressure Regulation Using LPV Techniques
Authors: Tasoujian Shahin , Grigoriadis Karolos , Franchek Matthew 
Published: November 2019

Abstract
This paper presents a delay-dependent parameter-varying control design approach to address the automated blood pressure regulation problem in the critical patient resuscitation using closed-loop administration of vasopressors. The mean arterial pressure (MAP) response of a patient subject to the intravenous vasoactive drug treatment is modeled as a linear parameter-varying (LPV) model, where varying model parameters and varying time-delay are considered as scheduling parameters of the system. Parameter-dependent Lyapunov-Krasovskii functionals are used to design an output-feedback dynamic controller to satisfy the closed-loop stability and reference MAP tracking requirements. The synthesis conditions are formulated in terms of Linear Matrix Inequalities (LMIs) that characterize the induced ℒ2-norm performance specification of the closed-loop system. The main objectives of the proposed control method in the presence of limitations posed by the time-varying model parameters and the large time-varying delay are to track the MAP reference command and maintain the blood pressure within the permissible range of commanded set-point, avoid undesirable overshoot and slow response, and to provide a smooth drug injection. Finally, to evaluate the performance of the proposed LPV blood pressure regulation approach, closed-loop simulations are conducted and the results confirm the effectiveness of the proposed control method against various simulated scenarios.
Model Predictive Control of Micro-CSP Integrated Into a Building HVAC System for Load Following Demand Response Programs
Authors: Toub Mohamed , Shahbakhti Mahdi , Robinett Rush D. , Aniba Ghassane 
Published: November 2019

Abstract
Building heat, ventilation and air conditioning (HVAC) systems are good candidates for demand response (DR) programs as they can flexibly alter their consumption to provide ancillary services to the grid and contribute to frequency and voltage regulation. One of the major ancillary services is the load following demand response (DR) program where the demand side tries to track a DR load profile required by the grid. This paper presents a real-time Model Predictive Control (MPC) framework for optimal operations of a micro-scale concentrated solar power (MicroCSP) system integrated into an office building HVAC system providing ancillary services to the grid. To decrease the energy cost of the building, the designed MPC exploits, along with the flexibility of the building’s HVAC system, the dispatching capabilities of the MicroCSP with thermal energy storage (TES) in order to control the power flow in the building and respond to the DR incentives sent by the grid. The results show the effect of incentives in the building participation to the load following DR program in the presence of a MicroCSP system and to what extent this participation is affected by seasonal weather variations and dynamic pricing.