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Issues
November 2024
ISSN 0022-0434
EISSN 1528-9028
In this Issue
Guest Editorial
Special Issue on Data-Driven Modeling and Control of Dynamical Systems
J. Dyn. Sys., Meas., Control. November 2024, 146(6): 060301.
doi: https://doi.org/10.1115/1.4066453
Topics:
Control modeling
,
Dynamic systems
,
Robotics
Special Papers
Velocity and Energy Consumption Prediction of Medium-Duty Electric Trucks Considering Road Features and Traffic Conditions
J. Dyn. Sys., Meas., Control. November 2024, 146(6): 061101.
doi: https://doi.org/10.1115/1.4065595
Topics:
Energy consumption
,
Roads
,
Traffic
,
Vehicles
,
Trucks
An Adjoint-Based Data-Driven Inverse-Free Iterative Feedforward Control Method
J. Dyn. Sys., Meas., Control. November 2024, 146(6): 061102.
doi: https://doi.org/10.1115/1.4065591
Topics:
Algorithms
,
Errors
,
Feedforward control
,
Trajectories (Physics)
,
Simulation
Inferring Human Control Intent Using Inverse Linear Quadratic Regulator With Output Penalty Versus Gain Penalty: Better Fit but Similar Intent
Heejin Yu, Ahmed Ramadan, Jacek Cholewicki, John M. Popovich, Jr., N. Peter Reeves, Joshua (Sung) H. You, Jongeun Choi
J. Dyn. Sys., Meas., Control. November 2024, 146(6): 061103.
doi: https://doi.org/10.1115/1.4065593
Topics:
Control equipment
,
Errors
,
Feedback
,
Goodness-of-fit tests
,
Human-robot interaction
,
Motor controls
,
Optimal control
,
Optimization
,
Performance
,
Robotics
Information-Theoretic Bayesian Inference for Multi-Agent Localization and Tracking of an Radio Frequency Target With Unknown Waveform
Nathaniel R. Olsen, Sasha M. McKee, Osama S. Haddadin, Scott M. Lyon, Jared E. Campbell, Kam K. Leang
J. Dyn. Sys., Meas., Control. November 2024, 146(6): 061104.
doi: https://doi.org/10.1115/1.4065592
Topics:
Algorithms
,
Errors
,
Sensors
,
Simulation
,
Particulate matter
,
Filters
Data-Driven Aircraft Modeling for Robust Reinforcement Learning Control Synthesis With Flight Test Validation
J. Dyn. Sys., Meas., Control. November 2024, 146(6): 061105.
doi: https://doi.org/10.1115/1.4065804
Topics:
Aircraft
,
Control equipment
,
Flight
,
Modeling
,
Dynamic models
,
Physics
Gaussian Process-Based Learning Control of Underactuated Balance Robots With an External and Internal Convertible Modeling Structure
J. Dyn. Sys., Meas., Control. November 2024, 146(6): 061106.
doi: https://doi.org/10.1115/1.4065937
Topics:
Design
,
Dynamics (Mechanics)
,
Errors
,
Pendulums
,
Robot dynamics
,
Robots
,
Trajectories (Physics)
,
Boundary element methods
,
Control equipment
,
Modeling
Learning Scalable Decentralized Controllers for Heterogeneous Robot Swarms With Graph Neural Networks
J. Dyn. Sys., Meas., Control. November 2024, 146(6): 061107.
doi: https://doi.org/10.1115/1.4065757
Topics:
Control equipment
,
Graph neural networks
,
Robots
,
Swarm robotics
Localization of Upstream Obstacles by Learning From Spectra of the Koopman Operator
J. Dyn. Sys., Meas., Control. November 2024, 146(6): 061108.
doi: https://doi.org/10.1115/1.4066009
Topics:
Algorithms
,
Convolutional neural networks
,
Eigenvalues
,
Flow (Dynamics)
,
Fluids
,
Hydrofoil
,
Pressure
,
Spectra (Spectroscopy)
,
Time series
,
Wakes
Optimal Control of Material Microstructures
J. Dyn. Sys., Meas., Control. November 2024, 146(6): 061109.
doi: https://doi.org/10.1115/1.4065801
Technical Briefs
Dynamic Mode Decomposition With Gaussian Process Regression for Control of High-Dimensional Nonlinear Systems
J. Dyn. Sys., Meas., Control. November 2024, 146(6): 064501.
doi: https://doi.org/10.1115/1.4065594
Topics:
Boundary layer turbulence
,
Dynamics (Mechanics)
,
Errors
,
Noise (Sound)
,
Nonlinear systems
,
Uncertainty
,
Predictive control
,
Trains
,
Modeling
Anti-Windup Adaptive Look-Up Table Algorithms With Application to Data-Driven Engine Controls
J. Dyn. Sys., Meas., Control. November 2024, 146(6): 064502.
doi: https://doi.org/10.1115/1.4065646
Topics:
Algorithms
,
Engines
,
Interpolation
,
Nitrogen oxides
,
Parameter estimation
,
Control systems
,
Errors
A Machine Learning Approach toward Cyber-Physical Security of Battery Systems
J. Dyn. Sys., Meas., Control. November 2024, 146(6): 064503.
doi: https://doi.org/10.1115/1.4065703
Topics:
Algorithms
,
Batteries
,
Sensors
,
Temperature
,
Testing
,
Cyber-attacks
,
Machine learning
,
Security
,
Resilience
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