bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Experimental Study of Longitudinal Tire Relaxation Constants for Vehicle Traction Dynamics Modeling
Authors: Vantsevich Vladimir V. , Demkiv Lyubomyr I. , Klos Sviatoslav R. , Misko Samuel R. , Moradi Lee 
Published: November 2019

Abstract
Existing literature on vehicle traction dynamics were reviewed for a variety of vehicle and tire dynamic models, some of which consider the pneumatic tires’ relaxation as a property of vehicle transient dynamics. In general, unlike the lateral relaxation counterpart, the longitudinal tire relaxation characteristics were mostly overlooked in tire transient dynamics modeling. As a continuation of the analytical study published in the 2018 DSCC Proceedings, the co-authors of this paper present an experimental study of the longitudinal tire relaxation characteristics of a Continental MPT 81 tire. Experimental results were obtained by conducting tests on an MTS Flat-Trac LTR tire testing machine. The experimental data is analyzed to investigate longitudinal tire relaxation characteristics as they relate to changes of tire conditions. The goal is to verify and refine the existing models suggested in the literature; as well as, discuss advantages and disadvantages of different test procedures and tire testing equipment.
In particular, the paper investigates the longitudinal tire relaxation constant variation due to changes of wheel velocity, tire inflation pressure, and sine oscillations of tire slippage in the time and frequency domains. The paper concludes on the influence of the longitudinal tire relaxation constants on the tire/vehicle traction dynamics modeling.
Comparison of Position Control With and Without Friction on a Foot Interface
Authors: Rudolph Brandon , Winck Ryder C. 
Published: November 2019

Abstract
A foot interface may one day control a third arm to assist the hands with a difficult task, but the interface needs to be easy to use. Developing a good foot interface is challenging because of the need to provide support for the leg, allow the user to disengage with the interface without causing unwanted motion, and make it easy for the user to hold a set position. The addition of friction in the interface can enable the device to meet these goals without negatively affecting performance. Although teleoperation is a well explored area of research, relatively little research has been done that examines the effects of friction on the control interface. This paper presents an experiment in which two foot control interfaces are compared. One device uses friction and the other has no added friction, so there is little resistance to motion in any direction. The experiment uses a reaching task and a path-following task to compare the interfaces. The only statistically significant performance differences were that the friction interface reduced the time needed to stop at a target and reduced excess movement when stopping at a target. Also, subjects indicated a preference for the friction interface. The results show that friction can be added to a foot interface to support the device and user and provide some positive gains in performance.
IMC-Based Calibration of the Boost Pressure Controller in an Electrically Assisted Turbocharged Gasoline Engine
Authors: Xiao Baitao , Kelly Tyler , Stolzenfeld Timothy , Lu Chenliu , Bell Dave , Jankovic Mrdjan , Buckland Julia , Rollinger John 
Published: November 2019

Abstract
In this work, a systematic approach is developed to calibrate a feedback controller for boost pressure control of an electrically assisted turbocharged gasoline engine. The information from the experiments indicates the system can be approximated by a Gain-Integrator-Delay (GID) model which can be robustly identified. Two controllers are designed for two different types of inner loop control (torque/speed) of the electrically assisted turbocharger. The underlying calibration methodology is based on Internal Model Control (IMC). The application of IMC leads to controllers that can be naturally mapped to a classic feedback controller. The plant model is obtained by characterizing the boost system with relay feedback experiments. The calibration methodology as well as the controller designs are demonstrated with a validated simulation platform and good performance is observed.
Completing Complex Contact Tasks Using Integrated Active and Passive Compliant Control Methodologies
Authors: Pettinger Adam , Pryor Mitch 
Published: November 2019

Abstract
In this paper we introduce the Generalized Contact Control Framework (GCCF) implemented on a compliant robotic manipulator. We demonstrate that the combined joint compliance and GCCF-based compliance control enable the completion of complex contact tasks in uncertain environments, where complex refers to the need to meet different contact force requirements involving multiple steps and output axes. Operating in uncertain environments means limited knowledge of the location or material properties of contact objects. The demonstrated tasks include opening a pill bottle and rigidly connecting to a purely mechanical tool changer. The GCCF simplifies the definition and modification of contact control parameters and allows for on-the-fly definition and completion of new tasks. Unlike hybrid force/impedance controllers, we do not need to define large damping and stiffness matrices, and we decouple the joint level control gains from the compliance control. The result is a robotic manipulator that can dynamically switch between unconstrained motion and contact tasks and provides a lot of versatility to perform a wide variety of tasks.
Hierarchical Nonlinear Moving Horizon Estimation of Vehicle Lateral Speed and Road Friction Coefficient
Authors: Jin Chi , Maitland Anson , McPhee John 
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/10.1115/1.4046395/1074688/Hierarchical-Nonlinear-Moving-Horizon-Estimation
Control-Oriented Model-Based Burn Duration and Ignition Timing Prediction With Recursive-Least-Square Adaptation for Closed-Loop Combustion Phasing Control of a Spark Ignition Engine
Authors: Wang Xin , Khameneian Amir , Dice Paul , Chen Bo , Shahbakhti Mahdi , Naber Jeffrey D. , Archer Chad , Qu Qiuping , Glugla Chris , Huberts Garlan 
Published: November 2019

Abstract
In homogeneous spark-ignition (SI) engines, ignition timing is used to control the combustion phasing (crank angle of fifty percent of fuel burned, CA50), which affects fuel economy, engine torque output, and emissions. This paper presents a model-based adaptive ignition timing prediction strategy using a control-oriented dynamic combustion model for real-time closed-loop combustion phasing control. The combustion model predicts the burn duration from ignition timing to CA50 (ΔθIGN-CA50) at Intake Valve Closing (IVC) for the upcoming cycle based on current engine operating conditions, including variable valve timing, predicted ignition timing, air-fuel ratio, engine speed, and engine load. To maintain the accuracy of combustion model and ignition timing prediction during the engine lifetime, a Recursive-Least-Square (RLS) with Variable Forgetting Factor (VFF) based adaptation algorithm is developed to handle both short term (operating-point-dependent) and long term (engine aging) model errors. Due to short term model errors and stochastic characteristics of cycle-to-cycle combustion variations, large model errors may occur during severe transient operating conditions (tip-in/tip-out), which can result in wrong adjustments and excessive adaptations. Since on-road SI engines are always operating in transient conditions, the ‘Heavy Transient Detection’ algorithm is developed to avoid fault adaptation and assist the adaptation algorithm to be stable. On-road vehicle testing data is used to evaluate the performance of the entire model-based adaptive burn duration and ignition timing prediction algorithm. With only 64 calibration points, a mean ignition timing prediction error of 0.2 Crank Angle Degree (CAD) and average iteration number of 2 shows the capability of adaptive ignition timing prediction, a significant reduction of calibration efforts, and potential of real-time application of the developed adaptive ignition timing prediction algorithm.
Generalization of Spectral Methods for High-Cycle Fatigue Analysis to Accommodate Non-Stationary Random Processes
Authors: Khalil Mohamed , Wüchner Roland , Bletzinger Kai-Uwe 
Published: November 2019

Abstract
Estimation of material fatigue life is an essential task in many engineering fields. When non-proportional loads are applied, the methodology to estimate fatigue life grows in complexity. Many methods have been proposed to solve this problem both in time and frequency domains. The former tends to give more accurate results, while the latter seems to be more computationally favorable. Until now, the focus of frequency-based methods has been limited to signals assumed to follow a stationary statistic process. This work proposes a generalization to the existing methods to accommodate non-stationary processes as well. A sensitivity analysis is conducted on the influence of the formulation’s hyper-parameters, followed by a numerical investigation on different signals and various materials to assert the robustness of the method.
Optimal Speed Control for a Connected and Autonomous Electric Vehicle Considering Battery Aging and Regenerative Braking Limits
Authors: Shao Yunli , Sun Zongxuan 
Published: November 2019

Abstract
This work develops a comprehensive optimal speed control framework for connected and autonomous electric vehicles considering both battery aging effects and regenerative braking limits. With the battery aging consideration, the energy benefits can be achieved together with a satisfactory battery life. The regenerative braking limits ensure the optimal control law is realistic and can be implemented in practice (e.g. there should be no regen when battery is almost full). The target vehicle intelligently controls the vehicle speed and car-following distance based on predicted traffic conditions using real-time information enabled by connectivity. The traffic prediction is based on a traffic flow model and can be implemented in a mixed-traffic scenario where both connected vehicles and non-connected vehicles share the road. The optimal control problem is formulated, simplified and discretized with minimal computational burden. It can be solved in real-time using an efficient nonlinear programming solver and is implemented in the model predictive control (MPC) fashion. The average computational time of the optimization is 0.54 seconds for a 15-second prediction horizon. A representative traffic scenario is evaluated in simulation where the target vehicle follows a vehicle platoon with 50% penetration rate of connectivity to pass a signalized roadway. The results show that 9.1% energy benefits can be obtained. The performance is satisfactory compared to 14.3% benefits with perfect traffic prediction.
Design and Control of a Power-Electronic Interface for Regenerative Suspension Systems
Authors: Algethami Abdullah A. , Kim Won-jong 
Published: November 2019

Abstract
Recently, the automobile industry has begun applying an increasing number of systems to recycling wasted energy. One area that demands further research is the recycling and storing of energy in car suspension systems, especially in terms of developing an electronic interface to keep energy flowing bidirectionally. An electronic interface was designed to facilitate control of regenerative forces and store energy after the rectification process. The electronic interface was designed to be a symmetrical-bridgeless boost converter, due to this mechanism having few components and requiring little control effort. The converter was created such that it kept the current and voltage in phase for the maximum power factor. The input into this controller was the generator voltage used to determine the polarity of the pulse-width modulation, considering external road disturbances. Thus, this combination of converter and controller was able to replace an active controller. Variable resistance could be further controlled to manipulate the suspension damping force.
Self-Reflective Learning Strategy for Persistent Autonomy of Aerial Manipulators
Authors: Zhou Xu , Zhang Jiucai , Zhang Xiaoli 
Published: November 2019

Abstract
Autonomous aerial manipulators have great potentials to assist humans or even fully automate manual labor-intensive tasks such as aerial cleaning, aerial transportation, infrastructure repair, and agricultural inspection and sampling. Reinforcement learning holds the promise of enabling persistent autonomy of aerial manipulators because it can adapt to different situations by automatically learning optimal policies from the interactions between the aerial manipulator and environments. However, the learning process itself could experience failures that can practically endanger the safety of aerial manipulators and hence hinder persistent autonomy. In order to solve this problem, we propose for the aerial manipulator a self-reflective learning strategy that can smartly and safely finding optimal policies for different new situations. This self-reflective manner consists of three steps: identifying the appearance of new situations, re-seeking the optimal policy with reinforcement learning, and evaluating the termination of self-reflection. Numerical simulations demonstrate, compared with conventional learning-based autonomy, our strategy can significantly reduce failures while still can finish the given task.
Online Nonlinear System Identification With Parameter Constraints: Application to Automotive Engine Systems
Authors: Chen Kaian , Li Zhaojian , Wang Yan , Wang Jing , Wu Kai , Filev Dimitar P. 
Published: November 2019

Abstract
In this paper, we treat the problem of online nonlinear system identification with parameter constraints. This approach is based upon our prior work on nonlinear system identification that exploits evolving Spatial-Temporal Filters (STF) to dynamically decompose system’s input/output space into a nonlinear combination of weighted local models. We extend the nonlinear system identification framework with the capability of dealing with linear equality and inequality parameter constraints. We leverage the gradient projection method in the local model parameter estimation process to inherently enforce the parameter constraints while retaining optimality. We apply the proposed algorithm to a turbo-charged gasoline engine system and promising results are demonstrated by experimental data.
Lifetime Optimization for a Grid-Friendly DC Fast Charge Station With Second Life Batteries
Authors: D’Arpino Matilde , Cancian Massimo 
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/10.1115/1.4046579/1075680/Lifetime-Optimization-for-a-Grid-Friendly-DC-Fast
On the Dynamics and Control of a Full Wrist Exoskeleton for Tremor Alleviation
Authors: Wang Jiamin , Barry Oumar , Kurdila Andrew J. , Vijayan Sujith 
Published: November 2019

Abstract
This paper introduces a novel wearable full wrist exoskeleton designed for the alleviation of tremor in patients suffering from Parkinson’s Disease and Essential Tremor. The design introduces a structure to provide full observation of wrist kinematics as well as actuation in wrist flexion/extension and radial/ulnar deviation. To examine the feasibility of the design, the coupled dynamics of the device and the forearm is modeled via a general multibody framework. The dynamic analysis considers human motion, wrist stiffness, and tremor dynamics. The analysis of the model reveals that the identification of the wrist kinematics is indispensable for the controller design. Nonlinear regression based on the Levenberg-Marquardt algorithm has been applied to estimate the unknown parameters in a kinematic structural function designed to approximate the wrist kinematics, which leads to the construction of the control system framework. Finally, several simulation cases are demonstrated to conclude the study.
Cooperative Transport of a Payload With Offset CG Using Multiple UAVs
Authors: Barawkar Shraddha , Kumar Manish 
Published: November 2019

Abstract
Cooperative transportation by multiple Unmanned Aerial Vehicles (UAVs) has been a topic of interest amongst robotics researchers since a decade. Researchers have developed different control schemes to address some of the issues related to cooperative transport. However, most of the existing control strategies assume a stationary center of gravity (CG) coinciding with the geometric center of the payload. In real world applications such as package delivery or human transport, position of CG, in general, would not be at geometric center, or would not be even known a – priori. This paper proposes a Proportional, Integral and Derivative (PID) controller to address the issue of control when the CG is offset during transportation of a common payload using multiple UAVs. The proposed PID scheme is centralized in nature in that it provides the same control action to all UAVs. Using extensive numerical simulations, the paper shows that such a scheme is shown to work effectively irrespective of the location of CG on the payload. The control scheme is also independent of the payload geometry and number of UAVs employed for cooperative transport. The work presented in this paper provides the groundwork to develop better control strategies to solve the problem of multi-UAV cooperative transport with a – priori unknown CG.
A Model Predictive Approach for the Coordination of Powertrain Control Systems
Authors: Stockar Stephanie , Rostiti Cristian , Canova Marcello , Prucka Michael 
Published: November 2019

Abstract
The design, calibration and integration of powertrain control algorithms has become significantly more complex in recent years, as the automotive industry faces increasing challenges in meeting consumer requirements and government regulations. Traditionally, the powertrain control engineering design process develops the engine and transmission controllers independently and then integrates them after an initial calibration. This process can lead to suboptimal performance and requires additional calibration and verification steps to improve the coordination of the various subsystems.
This paper proposes a novel approach to achieve a systematic, high-level coordination, and optimization of the control strategy in an automotive powertrain system that will reduce overall calibration effort. Optimized set-points for engine and transmission controls are generated based on joint optimization of fuel consumption and drivability using Model Predictive Control to manage both continuous and discrete control variables. Simulation results confirm the control decisions made by the proposed coordinator match a well-calibrated production ECU with little tuning effort.
A Real-Time Pressure Wave Model for Predicting Engine Knock
Authors: Li Ruixue C. , Zhu Guoming G. 
Published: November 2019

Abstract
This paper proposes a control-oriented pressure wave model, utilizing outputs of a reaction-based two-zone engine combustion model developed earlier, to accurately predict the key knock characteristics. The model can be used for model-based knock prediction and control. An in-cylinder pressure wave model of oscillation magnitude decay is proposed and simplified to describe pressure oscillations due to knock combustion, and the boundary and initial conditions of the pressure wave model at knock onset are provided by the two-zone reaction-based combustion model. The proposed pressure wave model is calibrated using experimental data, and the chemical kinetic-based Arrhenius integral (ARI) and maximum amplitude of pressure oscillations (MAPO) are used as the evaluation criteria for predicting knock onset and intensity, and the knock frequency is studied with the fast Fourier transform (FFT). The calibrated model is validated for predicting knock onset timing, knock intensity and frequency. Simulation results are compared with the experimental ones to demonstrate the capability of predicting engine knock characteristics by the proposed model.
Auto-Tuning Control of PEM Water Electrolyzer
Authors: Keow Alicia , Chen Zheng 
Published: November 2019

Abstract
Proton exchange membrane (PEM) electrolyzers with the ability to produce gases at a pressure suitable for direct metal hydride storage are desirable because they do not require the use of compressors and other auxiliary components. Direct storage into metal hydride cylinders is made feasible when the pressure and flow rate of hydrogen is controlled. The nonlinear dynamics of the PEM electrolyzer change with temperature and pressure, both of which change with the hydrogen production rate, and are thus difficult to estimate. Therefore, a model-free, relay-feedback, auto-tuning approach is used to tune a proportional integral (PI) controller. This allows for the determination of the voltage supply to the electrolyzer by tracking the current set-point and correlating it to the hydrogen production rate. A gain scheduling approach is used to record the tuned controller’s parameters at different set-points, minimizing the frequency of tuning the device. A self-assessment test is used to determine situations where the auto-tuner should activate to update the PI parameters, thus, allowing for the system to operate without supervision. The auto-tuning PI control is successfully tested with a PEM electrolyzer setup. Experimental results showed that an auto-tuner can tune the controller parameters and produce favorable transient behaviors, allowing for a degree of adaptability for variations in system set-points.
The Effects of Nylon Polymer Threads on Strain-Loading Hysteresis Behavior of Supercoiled Polymer (SCP) Artificial Muscles
Authors: Konda Revanth , Zhang Jun 
Published: November 2019

Abstract
Supercoiled polymers (SCP) actuator, as a recently discovered artificial muscle, has attracted a lot of attention as a compliant and compact actuation mechanism. SCP actuators can be fabricated from nylon polymer threads, and generates up to 20% strain under thermal activation. A common challenge, however, is to accurately and efficiently estimate the performance of SCP actuators considering their significant hysteresis among loading, strain, and power input. Previous studies adopted either linear models that failed to capture the hysteresis or phenomenological models that required tedious procedures for identification and implementation. In this paper, a physics-inspired model is presented to efficiently capture and estimate SCP actuators’ strain – loading hysteresis by analyzing the properties of nylon threads from which they are fabricated. The strains of SCP actuators are found to be linear to that of the nylon threads under the same loading conditions. An efficient approach is proposed to characterize and estimate the strain – loading hysteresis of SCP actuators fabricated with different numbers of nylon threads. A helical spring model is adopted to obtain the stiffness of SCP actuators with different configurations. Experimental validation involving two-ply, four-ply, and six-ply nylon threads and SCP actuators are provided to confirm the effectiveness of the proposed model.