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Proceedings Papers

A Novel Approach to Time Series Forecasting Using Model-Free Adaptive Control Framework

Meenakshi Narayan, Ann Majewicz Fey
Proc. ASME. DSCC2020, Volume 1: Adaptive/Intelligent Sys. Control; Driver Assistance/Autonomous Tech.; Control Design Methods; Nonlinear Control; Robotics; Assistive/Rehabilitation Devices; Biomedical/Neural Systems; Building Energy Systems; Connected Vehicle Systems; Control/Estimation of Energy Systems; Control Apps.; Smart Buildings/Microgrids; Education; Human-Robot Systems; Soft Mechatronics/Robotic Components/Systems; Energy/Power Systems; Energy Storage; Estimation/Identification; Vehicle Efficiency/Emissions, V001T12A002, October 5–7, 2020
Paper No: DSCC2020-3329
https://doi.org/10.1115/DSCC2020-3329
View Paper titled, A Novel Approach to Time Series Forecasting Using Model-Free Adaptive Control Framework
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Topics: Adaptive control, Time series, Algorithms, Computation, Control systems, Errors, Force sensors, Machine learning, Needles, Optimal control
Proceedings Papers

Bearing-Only Localization of a Quasi-Static Sound Source With a Binaural Microphone Array

Aidan J. Bradley, Masoud J. Shirazi, Nicole Abaid
Proc. ASME. DSCC2020, Volume 1: Adaptive/Intelligent Sys. Control; Driver Assistance/Autonomous Tech.; Control Design Methods; Nonlinear Control; Robotics; Assistive/Rehabilitation Devices; Biomedical/Neural Systems; Building Energy Systems; Connected Vehicle Systems; Control/Estimation of Energy Systems; Control Apps.; Smart Buildings/Microgrids; Education; Human-Robot Systems; Soft Mechatronics/Robotic Components/Systems; Energy/Power Systems; Energy Storage; Estimation/Identification; Vehicle Efficiency/Emissions, V001T21A005, October 5–7, 2020
Paper No: DSCC2020-3235
https://doi.org/10.1115/DSCC2020-3235
View Paper titled, Bearing-Only Localization of a Quasi-Static Sound Source With a Binaural Microphone Array
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Topics: Bearings, Microphone arrays, Robots, Sensors, Anechoic chambers, Dynamic models, Engineering prototypes, Engineers, Machine learning, Robotics
Proceedings Papers

Identification of Temperature Dynamics Using Subspace and Machine Learning Techniques

Aleksandar Haber, Francesco Pecora, Mobin Uddin Chowdhury, Melvin Summerville
Proc. ASME. DSCC2019, Volume 2: Modeling and Control of Engine and Aftertreatment Systems; Modeling and Control of IC Engines and Aftertreatment Systems; Modeling and Validation; Motion Planning and Tracking Control; Multi-Agent and Networked Systems; Renewable and Smart Energy Systems; Thermal Energy Systems; Uncertain Systems and Robustness; Unmanned Ground and Aerial Vehicles; Vehicle Dynamics and Stability; Vibrations: Modeling, Analysis, and Control, V002T24A003, October 8–11, 2019
Paper No: DSCC2019-9007
https://doi.org/10.1115/DSCC2019-9007
View Paper titled, Identification of Temperature Dynamics Using Subspace and Machine Learning Techniques
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Topics: Dynamics (Mechanics), Machine learning, Temperature, Actuators, Aluminum, Control engineering, Experimental design, Heat, Noise control, Thermocouples
Proceedings Papers

Machine-Learning Based Thermal-Geometric Predictive Modeling of Laser Powder Bed Fusion Additive Manufacturing

Yong Ren, Qian Wang, Pan Michaleris
Proc. ASME. DSCC2019, Volume 1: Advanced Driver Assistance and Autonomous Technologies; Advances in Control Design Methods; Advances in Robotics; Automotive Systems; Design, Modeling, Analysis, and Control of Assistive and Rehabilitation Devices; Diagnostics and Detection; Dynamics and Control of Human-Robot Systems; Energy Optimization for Intelligent Vehicle Systems; Estimation and Identification; Manufacturing, V001T10A001, October 8–11, 2019
Paper No: DSCC2019-8995
https://doi.org/10.1115/DSCC2019-8995
View Paper titled, Machine-Learning Based Thermal-Geometric Predictive Modeling of Laser Powder Bed Fusion Additive Manufacturing
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Topics: Additive manufacturing, Lasers, Machine learning, Modeling, Temperature, Simulation, Algorithms, Artificial neural networks, Computation, Physics
Proceedings Papers

Kinect-Based Human Gait Recognition Using a Novel Adaptive Dynamics Learning Approach

Xiaotian Chen, Paolo Stegagno, Xiaonan Dong, Chengzhi Yuan
Proc. ASME. DSCC2019, Volume 1: Advanced Driver Assistance and Autonomous Technologies; Advances in Control Design Methods; Advances in Robotics; Automotive Systems; Design, Modeling, Analysis, and Control of Assistive and Rehabilitation Devices; Diagnostics and Detection; Dynamics and Control of Human-Robot Systems; Energy Optimization for Intelligent Vehicle Systems; Estimation and Identification; Manufacturing, V001T09A001, October 8–11, 2019
Paper No: DSCC2019-8920
https://doi.org/10.1115/DSCC2019-8920
View Paper titled, Kinect-Based Human Gait Recognition Using a Novel Adaptive Dynamics Learning Approach
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Topics: Adaptive dynamics, Dynamics (Mechanics), Algorithms, Databases, Graphical user interfaces, Machine learning, Robots, Visualization
Proceedings Papers

Foveation Control of a Robotic Eye Using Deep Reinforcement Learning

Sunil Kumar Rajendran, Qi Wei, Feitian Zhang
Proc. ASME. DSCC2018, Volume 1: Advances in Control Design Methods; Advances in Nonlinear Control; Advances in Robotics; Assistive and Rehabilitation Robotics; Automotive Dynamics and Emerging Powertrain Technologies; Automotive Systems; Bio Engineering Applications; Bio-Mechatronics and Physical Human Robot Interaction; Biomedical and Neural Systems; Biomedical and Neural Systems Modeling, Diagnostics, and Healthcare, V001T04A018, September 30–October 3, 2018
Paper No: DSCC2018-9209
https://doi.org/10.1115/DSCC2018-9209
View Paper titled, Foveation Control of a Robotic Eye Using Deep Reinforcement Learning
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Topics: Robotics, Design, Muscle, Biomechanics, Dynamic models, Machine learning, Motion control, Polymers, Simulation
Proceedings Papers

Learning to Predict Coronary Perfusion Pressure During Cardiopulmonary Resuscitation

Manan Gandhi, Yunpeng Pan, Evangelos Theodorou, Pierre Sebastian, Matt Olson, Demetri Yannopoulos
Proc. ASME. DSCC2018, Volume 1: Advances in Control Design Methods; Advances in Nonlinear Control; Advances in Robotics; Assistive and Rehabilitation Robotics; Automotive Dynamics and Emerging Powertrain Technologies; Automotive Systems; Bio Engineering Applications; Bio-Mechatronics and Physical Human Robot Interaction; Biomedical and Neural Systems; Biomedical and Neural Systems Modeling, Diagnostics, and Healthcare, V001T13A002, September 30–October 3, 2018
Paper No: DSCC2018-8968
https://doi.org/10.1115/DSCC2018-8968
View Paper titled, Learning to Predict Coronary Perfusion Pressure During Cardiopulmonary Resuscitation
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Topics: Pressure, Algorithms, Delays, Filtration, Linear systems, Machine learning, Modeling
Proceedings Papers

Human Intention Estimation With Tactile Sensors in Human-Robot Collaboration

Yiwei Wang, Yixuan Sheng, Ji Wang, Wenlong Zhang
Proc. ASME. DSCC2017, Volume 2: Mechatronics; Estimation and Identification; Uncertain Systems and Robustness; Path Planning and Motion Control; Tracking Control Systems; Multi-Agent and Networked Systems; Manufacturing; Intelligent Transportation and Vehicles; Sensors and Actuators; Diagnostics and Detection; Unmanned, Ground and Surface Robotics; Motion and Vibration Control Applications, V002T04A007, October 11–13, 2017
Paper No: DSCC2017-5291
https://doi.org/10.1115/DSCC2017-5291
View Paper titled, Human Intention Estimation With Tactile Sensors in Human-Robot Collaboration
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Topics: Collaboration, Robots, Tactile sensors, Manipulators, Algorithms, Grippers, Machine learning, Paper machines, Path planning
Proceedings Papers

An Inertial Sensor to Measure Wind Turbulence With RC Helicopters

Anil Kumar, Pinhas Ben-Tzvi
Proc. ASME. DSCC2017, Volume 3: Vibration in Mechanical Systems; Modeling and Validation; Dynamic Systems and Control Education; Vibrations and Control of Systems; Modeling and Estimation for Vehicle Safety and Integrity; Modeling and Control of IC Engines and Aftertreatment Systems; Unmanned Aerial Vehicles (UAVs) and Their Applications; Dynamics and Control of Renewable Energy Systems; Energy Harvesting; Control of Smart Buildings and Microgrids; Energy Systems, V003T39A010, October 11–13, 2017
Paper No: DSCC2017-5354
https://doi.org/10.1115/DSCC2017-5354
View Paper titled, An Inertial Sensor to Measure Wind Turbulence With RC Helicopters
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Topics: Helicopters, Sensors, Turbulence, Wind, Dynamics (Mechanics), Telemetry, Algorithms, Blades, Fans, Machine learning
Proceedings Papers

Systematic Feature Selection Process Applied in Short-Term Data-Driven Building Energy Forecasting Models: A Case Study of a Campus Building

Liang Zhang, Jin Wen, Yimin Chen
Proc. ASME. DSCC2017, Volume 3: Vibration in Mechanical Systems; Modeling and Validation; Dynamic Systems and Control Education; Vibrations and Control of Systems; Modeling and Estimation for Vehicle Safety and Integrity; Modeling and Control of IC Engines and Aftertreatment Systems; Unmanned Aerial Vehicles (UAVs) and Their Applications; Dynamics and Control of Renewable Energy Systems; Energy Harvesting; Control of Smart Buildings and Microgrids; Energy Systems, V003T27A002, October 11–13, 2017
Paper No: DSCC2017-5073
https://doi.org/10.1115/DSCC2017-5073
View Paper titled, Systematic Feature Selection Process Applied in Short-Term Data-Driven Building Energy Forecasting Models: A Case Study of a Campus Building
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Topics: Feature selection, Computation, Errors, Machine learning, Modeling, Sensors, Statistics, Structures
Proceedings Papers

Classification of Muscular Nonfatigue and Fatigue Conditions Using Surface EMG Signals and Fractal Algorithms

Kiran Marri, Ramakrishnan Swaminathan
Proc. ASME. DSCC2016, Volume 1: Advances in Control Design Methods, Nonlinear and Optimal Control, Robotics, and Wind Energy Systems; Aerospace Applications; Assistive and Rehabilitation Robotics; Assistive Robotics; Battery and Oil and Gas Systems; Bioengineering Applications; Biomedical and Neural Systems Modeling, Diagnostics and Healthcare; Control and Monitoring of Vibratory Systems; Diagnostics and Detection; Energy Harvesting; Estimation and Identification; Fuel Cells/Energy Storage; Intelligent Transportation, V001T10A002, October 12–14, 2016
Paper No: DSCC2016-9828
https://doi.org/10.1115/DSCC2016-9828
View Paper titled, Classification of Muscular Nonfatigue and Fatigue Conditions Using Surface EMG Signals and Fractal Algorithms
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Topics: Algorithms, Electromyography, Fatigue, Fractals, Signals, Muscle, Genetic algorithms, Biomedicine, Density, Dimensions
Proceedings Papers

Smartphone-Based Wheel Imbalance Detection

Joshua E. Siegel, Rahul Bhattacharyya, Sanjay Sarma, Ajay Deshpande
Proc. ASME. DSCC2015, Volume 2: Diagnostics and Detection; Drilling; Dynamics and Control of Wind Energy Systems; Energy Harvesting; Estimation and Identification; Flexible and Smart Structure Control; Fuels Cells/Energy Storage; Human Robot Interaction; HVAC Building Energy Management; Industrial Applications; Intelligent Transportation Systems; Manufacturing; Mechatronics; Modelling and Validation; Motion and Vibration Control Applications, V002T19A002, October 28–30, 2015
Paper No: DSCC2015-9716
https://doi.org/10.1115/DSCC2015-9716
View Paper titled, Smartphone-Based Wheel Imbalance Detection
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Topics: Wheels, Vehicles, Accelerometers, Excitation, Flaw detection, Fourier transforms, Machine learning, Principal component analysis, Roads, Sensors
Proceedings Papers

A Performance Comparison of EMG Classification Methods for Hand and Finger Motion

Sungtae Shin, Reza Langari, Reza Tafreshi
Proc. ASME. DSCC2014, Volume 2: Dynamic Modeling and Diagnostics in Biomedical Systems; Dynamics and Control of Wind Energy Systems; Vehicle Energy Management Optimization; Energy Storage, Optimization; Transportation and Grid Applications; Estimation and Identification Methods, Tracking, Detection, Alternative Propulsion Systems; Ground and Space Vehicle Dynamics; Intelligent Transportation Systems and Control; Energy Harvesting; Modeling and Control for Thermo-Fluid Applications, IC Engines, Manufacturing, V002T16A008, October 22–24, 2014
Paper No: DSCC2014-5993
https://doi.org/10.1115/DSCC2014-5993
View Paper titled, A Performance Comparison of EMG Classification Methods for Hand and Finger Motion
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Topics: Electromyography, Algorithms, Dimensions, Feature extraction, Pattern recognition, Trains, Discrete wavelet transforms, Machine learning, Multilayer perceptron, Principal component analysis
Proceedings Papers

Prediction of ICU In-Hospital Mortality Using Artificial Neural Networks

Henian Xia, Nathan Keeney, Brian J. Daley, Adam Petrie, Xiaopeng Zhao
Proc. ASME. DSCC2013, Volume 3: Nonlinear Estimation and Control; Optimization and Optimal Control; Piezoelectric Actuation and Nanoscale Control; Robotics and Manipulators; Sensing; System Identification (Estimation for Automotive Applications, Modeling, Therapeutic Control in Bio-Systems); Variable Structure/Sliding-Mode Control; Vehicles and Human Robotics; Vehicle Dynamics and Control; Vehicle Path Planning and Collision Avoidance; Vibrational and Mechanical Systems; Wind Energy Systems and Control, V003T43A001, October 21–23, 2013
Paper No: DSCC2013-3768
https://doi.org/10.1115/DSCC2013-3768
View Paper titled, Prediction of ICU In-Hospital Mortality Using Artificial Neural Networks
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Topics: Algorithms, Artificial neural networks, Databases, Drugs, Feature selection, Machine learning, Machinery, Neural network models, Optimization, Physiology
Proceedings Papers

Fast Modeling and Identification of Robot Dynamics Using the Lasso

Cong Wang, Xiaowen Yu, Masayoshi Tomizuka
Proc. ASME. DSCC2013, Volume 3: Nonlinear Estimation and Control; Optimization and Optimal Control; Piezoelectric Actuation and Nanoscale Control; Robotics and Manipulators; Sensing; System Identification (Estimation for Automotive Applications, Modeling, Therapeutic Control in Bio-Systems); Variable Structure/Sliding-Mode Control; Vehicles and Human Robotics; Vehicle Dynamics and Control; Vehicle Path Planning and Collision Avoidance; Vibrational and Mechanical Systems; Wind Energy Systems and Control, V003T39A002, October 21–23, 2013
Paper No: DSCC2013-3767
https://doi.org/10.1115/DSCC2013-3767
View Paper titled, Fast Modeling and Identification of Robot Dynamics Using the Lasso
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Topics: Modeling, Robot dynamics, Robots, Belts, Machine learning