Journal of Dynamic Systems, Measurement, and Control
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EISSN:1528-9028|ISSN:0022-0434|Disc:The Journal of Dynamic Systems, Measurement, and Control publishes theoretical and applied original papers in the traditional areas implied by its name, as well as papers in interdisciplinary areas. Theoretical papers should present new theoretical developments and knowledge for controls of dynamical systems together with clear engineering motivation for the new theory. New theory or results that are only of mathematical interest without a clear engineering motivation or have a cursory relevance only are discouraged. "Application" is understood to include modeling, simulation of realistic systems, and corroboration of theory with emphasis on demonstrated practicality.|Priority:12|Publisher:American Society of Mechanical Engineers|
Recent Submissions
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A Machine Learning Approach toward Cyber-Physical Security of Battery Systems
(The American Society of Mechanical Engineers (ASME), 2024)Modern battery systems exhibit a cyber-physical nature due to the extensive use of communication technologies in battery management. This makes modern cyber-physical battery systems vulnerable to cyber threats where an ... -
Anti-Windup Adaptive Look-Up Table Algorithms With Application to Data-Driven Engine Controls
(The American Society of Mechanical Engineers (ASME), 2024)This technical brief presents anti-windup adaptation algorithms for a look-up table (LUT), widely used in data-driven engine control systems to accurately model complex features while minimizing computational demand. Engine ... -
Dynamic Mode Decomposition With Gaussian Process Regression for Control of High-Dimensional Nonlinear Systems
(The American Society of Mechanical Engineers (ASME), 2024)In this work, we consider the problem of learning a reduced-order model of a high-dimensional stochastic nonlinear system with control inputs from noisy data. In particular, we develop a hybrid parametric/nonparametric ... -
Optimal Control of Material Microstructures1
(The American Society of Mechanical Engineers (ASME), 2024)In this paper, we consider the optimal control of material microstructures. Such material microstructures are modeled by the so-called phase-field model. We study the underlying physical structure of the model and propose ... -
Localization of Upstream Obstacles by Learning From Spectra of the Koopman Operator
(The American Society of Mechanical Engineers (ASME), 2024)Objects moving in water or stationary objects in streams create a vortex wake. An underwater robot encountering the wake created by another body experiences disturbance forces and moments. These disturbances can be associated ... -
Learning Scalable Decentralized Controllers for Heterogeneous Robot Swarms With Graph Neural Networks
(The American Society of Mechanical Engineers (ASME), 2024)Distributed multi-agent systems are becoming increasingly crucial for diverse applications in robotics because of their capacity for scalability, efficiency, robustness, resilience, and the ability to accomplish complex ... -
Gaussian Process-Based Learning Control of Underactuated Balance Robots With an External and Internal Convertible Modeling Structure
(The American Society of Mechanical Engineers (ASME), 2024)External and internal convertible (EIC) form-based motion control is one of the effective designs of simultaneous trajectory tracking and balance for underactuated balance robots. Under certain conditions, the EIC-based ... -
Data-Driven Aircraft Modeling for Robust Reinforcement Learning Control Synthesis With Flight Test Validation
(The American Society of Mechanical Engineers (ASME), 2024)Low-fidelity engineering-level dynamic models are commonly employed while designing uncrewed aircraft flight controllers due to their rapid development and cost-effectiveness. However, during adverse conditions, or complex ... -
Information-Theoretic Bayesian Inference for Multi-Agent Localization and Tracking of an Radio Frequency Target With Unknown Waveform
(The American Society of Mechanical Engineers (ASME), 2024)Information-theoretic motion planning and machine learning through Bayesian inference are exploited to localize and track a dynamic radio frequency (RF) emitter with unknown waveform (uncooperative target). A target-state ... -
Inferring Human Control Intent Using Inverse Linear Quadratic Regulator With Output Penalty Versus Gain Penalty: Better Fit but Similar Intent
(The American Society of Mechanical Engineers (ASME), 2024)To identify the underlying mechanisms of human motor control, parametric models are utilized. One approach of employing these models is the inferring the control intent (estimating motor control strategy). A well-accepted ... -
An Adjoint-Based Data-Driven Inverse-Free Iterative Feedforward Control Method
(The American Society of Mechanical Engineers (ASME), 2024)Feedforward control is widely used in control systems since it can achieve high tracking performance by effectively compensating for known disturbances before they affect the system. For traditional feedforward control ... -
Velocity and Energy Consumption Prediction of Medium-Duty Electric Trucks Considering Road Features and Traffic Conditions
(The American Society of Mechanical Engineers (ASME), 2024)Electric vehicles (EVs) have emerged as a promising solution to address environmental concerns, especially benefiting urban delivery and last-mile fleets due to their unique operational characteristics. Despite the potential ... -
State Identification Via Symbolic Time Series Analysis for Reinforcement Learning Control
(The American Society of Mechanical Engineers (ASME), 2024)This technical brief makes use of the concept of symbolic time-series analysis (STSA) for identifying discrete states from the nonlinear time response of a chaotic dynamical system for model-free reinforcement learning ... -
Continuous-Time Algebraic Riccati Equation Solution for Second-Order Systems
(The American Society of Mechanical Engineers (ASME), 2024)The continuous-time algebraic Riccati equation (ARE) is often utilized in control, estimation, and optimization. For a linear system with a second-order structure of size n, the ARE required to be solved to get the control ... -
Reduced-Order Model Parameterization for Uncertain LTI SISO Systems
(The American Society of Mechanical Engineers (ASME), 2024)The primary goal of this paper is to develop a formal foundation to design an adaptive output feedback predictor for a class of unknown systems where parameters and order are unknown or high-dimensional. We present a ... -
Convex Optimization Based Design of Finite Impulse Response Filters for Reference Shaping
(The American Society of Mechanical Engineers (ASME), 2024)This paper explores design of finite impulse response (FIR) filters for controlling underdamped systems while dealing with uncertainties in model parameters. By setting magnitude constraints in the frequency domain within ... -
Offset-Free Koopman Model Predictive Control of Thermal Comfort Regulation for a Variable Refrigerant Flow-Dedicated Outdoor Air System-Combined System
(The American Society of Mechanical Engineers (ASME), 2024)Variable refrigerant flow (VRF) system has been an appealing solution of air conditioning for residential and commercial buildings, due to its flexibility and cost effectiveness, while lack of ventilation capability is a ... -
Reactive Gait Composition With Stability: Dynamic Walking Amidst Static and Moving Obstacles
(The American Society of Mechanical Engineers (ASME), 2024)This paper presents a modular approach to motion planning with provable stability guarantees for robots that move through changing environments via periodic locomotion behaviors. We focus on dynamic walkers as a paradigm ... -
Integral Sliding Mode Disturbance Observer-Based Preview Repetitive Control
(The American Society of Mechanical Engineers (ASME), 2024)This paper deals with the problem of integral sliding mode disturbance observer (ISDOB)-based preview repetitive control (PRC) for a class of nonlinear systems subject to external disturbances and nonlinearity. First, an ... -
A Time Headway Control Scheme for Virtually Coupled Heavy Haul Freight Trains
(The American Society of Mechanical Engineers (ASME), 2024)Virtual coupling of railway trains is an emerging technology that has the potential to significantly increase railway operational efficiency by reducing the train following distance from absolute braking distances to ...
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