With the vigorous development of mechanical intelligence in industrial manufacturing, tracking control dynamic systems have been widely applied in many aspects of industry. In this paper, we present one theorem to discuss the validity condition of a...
We explore the analogy between the asymptotic (high Reynolds number) scaling of two canonical wall-bounded turbulent flows, namely zero-pressure-gradient (ZPG) and pipe flows. We find that the two flows can be characterised using similar scaling laws...
In this paper, a gradient dynamics-based control method is proposed to directly tackle the singularity problem in the backstepping control design of the TORA system. This method is founded upon the construction of an energy-like positive function, wh...
Federated learning represents a newly emerging methodology in the field of machine learning that enables distributed agents to collaboratively learn a centralized model without sharing their raw data. Some scholars have already proposed many first-or...
We study whether overparameterized neural networks can learn to satisfy pointwise constraints without inductive bias. One might expect that a sufficiently expressive network would learn to respect such constraints. We prove that this is not the case....
Series-winding three-phase PMSMs have a higher bus voltage utilization than the conventional three-phase PMSMs with star connection. This topology is suitable for applications with a limited bus voltage. However, the zero-sequence current controller...
In the present work, the steady-state stationary thermal convection of moist saturated air in a lower atmosphere has been studied theoretically. Thermal convection was considered without accounting for the Coriolis force, and with only the vertical t...
The speed-gradient variational principle (SG-principle) for nonstationary far from equilibrium systems is formulated and illustrated by examples. The SG-model of transient (relaxation) dynamics for systems of a finite number of particles based on max...
CO2 geosequestration is an important contributor to United Nations Sustainable Development Goal 13, i.e., Climate Action, which states a global Net-Zero CO2 emissions by 2050. A potential impact of CO2 geosequestration in depleted oil and gas reservo...
Experimental results are compiled to show apparent hysteresis seen in hydride thermal precipitation–dissolution cycling in zirconium alloys using X-ray diffraction, dynamic elastic modulus techniques, and differential scanning calorimetry (DSC)...
Due to the time delay and some unavoidable noise factors, obtaining a real-time solution of dynamic time-varying linear matrix equation (LME) problems is of great importance in the scientific and engineering fields. In this paper, based on the philos...
The geometric complexity and high-pressure gradients that characterize the design of the flow field of gear pumps make it very difficult to obtain an accurate CFD simulation of the component. Usually, assumptions are made both in terms of geometrical...
Complex distribution-network topologies limit the accuracy of traveling-wave fault location, because the zero-mode velocity decays nonlinearly while conventional double-ended methods still require synchronized clocks. A clock-offset-invariant multi-t...
The interaction of a turbulent, spatially developing crossflow with a transverse jet possesses several engineering and technological applications such as film cooling of turbine blades, exhaust plumes, thrust vector control, fuel injection, etc. Dire...
A transient stability flow analysis is performed using the unsteady laminar boundary layer equations. The flow dynamics are studied via the Navier–Stokes equations. In the case of external spatially developing flow, the differential equations a...
Activation functions are fundamental to the representational capacity and optimization dynamics of deep neural networks. Although numerous nonlinearities have been proposed, ranging from classical sigmoid and tanh to modern smooth and trainable funct...
Multi-lane overtaking among mixed-size vehicles produces highly transient aerodynamic interactions that challenge vehicle stability. This study investigates the unsteady aerodynamic response of a heavy-duty truck, an SUV, and a passenger sedan during...
Zeroing neural networks (ZNN), as a specialized class of bio-Iinspired neural networks, emulate the adaptive mechanisms of biological systems, allowing for continuous adjustments in response to external variations. Compared to traditional numerical m...
This paper introduces a robust waveform design method aimed at reducing the impact of electromagnetic interference in radar systems, thereby enhancing target detection accuracy. We propose utilizing a high-order p-norm to characterize the peak sidelo...
We report on an advanced density-functional theory (DFT) approach for investigating the ground-state and thermodynamical properties of uranium mononitride (UN). The electronic structure for UN at zero temperature is obtained from DFT that utilizes th...
This work addresses a pattern-moving-based partial form dynamic linearization model free adaptive control (P-PFDL-MFAC) scheme and illustrates the bounded convergence of its tracking error for a class of unknown nonaffine nonlinear discrete-time syst...
This paper introduces a sociotropy-inspired game-theoretic framework for distributed multiple-input multiple-output (MIMO) beamforming systems, where each antenna element is modeled as a strategic agent that adapts its beamforming parameters by balan...
This paper presents an approach for the solution of a zero-sum differential game associated with a nonlinear state-feedback
Federated learning (FL) has emerged as an important distributed machine learning paradigm allowing many users to train a model together without sharing raw data. However, FL’s decentralized design makes it very susceptible to both Byzantine and...
An experimental investigation is performed to elucidate the variations of accelerations and pressure gradients in the external stream of retreating flow during the run-down phase of a non-breaking solitary wave, propagating over a 1:3 sloping beach....
This study investigates the (
In turbine blade environments, the combination of blade curvature and accelerating flow gives rise to streamwise pressure gradients (SPGs), which substantially impact coolant–mainstream interactions. This study investigates the effect of SPGs o...
This study aims to clarify how porosity and frequency interact to influence permeability and flow behavior in porous media subjected to sinusoidal pressure variations. Specifically, we investigate oscillatory flow at 1 Hz and 100 Hz under varying por...
This paper aims to describe a synthesis procedure for discrete-time, energy-based regulators for continuous-time port-Hamiltonian systems. The methodology consists of three steps. The first deals with the definition of a discrete-time approximation o...
Air temperature (
Mini-electric trucks have been widely used because of their high efficiency and zero emission with the rapid development of electronic commerce and express industry. So, improvement of dynamic performance and economy becomes crucial. The research in...
High-speed turbulent boundary layers govern the transport of momentum, mass, and energy in compressible flows and play a central role in determining aerodynamic performance, skin-friction drag, aerodynamic heating, flow stability, and thermal protect...
Pedestrian flow prediction is a quintessential time series forecasting problem with widespread applications in domains such as indoor navigation and emergency response. However, existing prediction models exhibit sensitivity to anomalous data and fac...
Autonomous stealth navigation through modern Integrated Air Defense Systems requires Unmanned Aerial Vehicles (UAVs) to minimize radar detectability while maintaining efficient flight. This poses a severe continuous-control challenge under partial ob...
This paper investigates the filtering problem for multivariate continuous nonlinear non-Gaussian systems based on an improved minimum error entropy (MEE) criterion. The system is described by a set of nonlinear continuous equations with non-Gaussian...
In this article, to study the influence of neural networks’ morphology symmetry, a mathematical model is developed that considers dynamic symmetry for diagnosing complex dynamic objects. The developed mathematical model includes the symmetric a...
Autonomous driving in dense traffic demands policies that ensure safety, accurate path tracking, and ride comfort, yet reinforcement learning (RL) alone suffers from low sample efficiency and weak safety guarantees, while classical artificial potenti...
Cross-domain data collaboration is a core requirement for the intelligent development of critical areas such as the Internet of Vehicles and intelligent transportation systems. In this scenario, vehicles and various sensors deployed roadside continuo...
Zero-day attacks pose a persistent threat to computing infrastructure by exploiting previously unknown software vulnerabilities that evade traditional signature-based network intrusion detection systems (NIDSs). To address this limitation, machine le...
This research introduces a robust control design for multibody robot systems, incorporating sliding mode control (SMC) for robustness against uncertainties and disturbances. SMC achieves this through directing system states toward a predefined slidin...
Predicting near-future monetization in virtual livestreaming remains methodologically challenging because paid-support events are sparse, temporally dependent, and vulnerable to leakage under inappropriate evaluation designs. This study develops a le...
The transition toward disaggregated, software-defined 5G Standalone (SA) infrastructures has shifted much of the end-to-end latency budget from the radio interface into the transport and computational layers, where bufferbloat and congestion-window c...
The success of DNA amplification in Polymerase Chain Reaction (PCR) devices inherently depends on the rapid and absolute zero-overshoot temperature control of thermoelectric cooler (TEC) systems. In the literature, metaheuristic algorithms employed f...
The density functional theory (DFT) framework in the generalized gradient approximation (GGA) was employed to study the mechanical, dynamical, and thermodynamic properties of the ordered bimetallic Fe-Pt alloys with stoichiometric structures Fe3Pt, F...
This article presents the synthesis, real-time implementation, and experimental validation of an approximated adaptive dynamic programming (AADP) actor–critic controller for precise flow rate regulation of a variable-displacement axial-piston p...
Machine learning (ML) is an effective tool to interrogate complex systems to find optimal parameters more efficiently than through manual methods. This efficiency is particularly important for systems with complex dynamics between multiple parameters...
Based on the framework of our previous work [H.L. Lai et al., Phys. Rev. E, 94, 023106 (2016)], we continue to study the effects of Knudsen number on two-dimensional Rayleigh–Taylor (RT) instability in compressible fluid via the discrete Boltzm...
Accurate deflection prediction is vital for structural health monitoring of large-span bridges yet remains challenging due to complex nonlinear environmental couplings. This paper proposes a hybrid deep learning framework, BGCO-PIC-DA-LSTM, for preci...
Mass balance observations are beneficial for assessing climate change in different world regions. This study analyzed the glacier elevation change, ice flux divergence, and surface mass balance (SMB) in the West Kunlun Mountains (WKM) on the Tibetan...
Myriapods achieve remarkable obstacle-crossing capability through inter-segment pitch adjustment and coordinated anterior–posterior propulsion, providing valuable biomimetic inspiration for engineering design. Articulated tracked vehicles, conn...
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