China is one of the world’s largest tea-producing countries, and its fluctuations in production affect the international market and domestic economic stability. Existing research often uses limited predictive models at the local scale and lacks...
This study targets the low accuracy and efficiency of the support vector machine (SVM) algorithm in rolling bearing fault diagnosis. An improved grey wolf optimizer (IGWO) algorithm was proposed based on deep learning and a swarm intelligence optimiz...
Roll motion induced by steering maneuvers and vertical vibration excited by road unevenness are strongly coupled in active suspension vehicles. Neglecting this coupling may deteriorate the performance of coordinated chassis control and compromise bot...
A tuned rolling mass damper system (TRMD) is newly combined with structural hollow slabs to act as an ensemble passive damping device to mitigate structural responses. The main advantage of this controlled configuration lies in its capacity to mainta...
This paper presents ROTOTILLER (Rolling Optimization of Tasks and Online Trajectories Integrating Local Lookahead Extended Routing), an extension of the extended-SPADES framework for integrated task allocation and fleet navigation in dynamic logistic...
Dynamic events require coordinated task allocation (TA) and path planning (PP) for multiple unmanned aerial vehicles (UAVs) to maintain executable mission progress. Existing coupled methods often use path information only as a precomputed cost or dow...
A model predictive control (MPC) strategy is proposed based on state observation and updating for image-based visual servoing (IBVS) tasks of micro aerial vehicles (MAVs). This control strategy enables precise pose adjustment of MAVs without relying...
The accurate acquisition and real-time calculation of the attitude angle of precision firefighting extinguishing projectiles are essential for ensuring stable flight and precise extinguishing agent release. However, measuring the roll attitude angle...
As an important part of urban terminal delivery, automated guided vehicles (AGVs) have been widely used in the field of takeout delivery. Due to the real-time generation of takeout orders, the delivery system is required to be extremely dynamic, so t...
It is difficult to accurately extract the health index of non-stationary signals of rolling bearings under variable rotational speed, which also leads to greater prediction error for bearing degradation models with fixed parameters. For this reason,...
The environmental factors of greenhouses affect crop growth greatly and are mutually coupled and spatially distributed. Due to the complexity of greenhouse climate modeling, the current optimal control of greenhouse crop growth rarely considers the s...
This paper proposes a feedback, rolling and adaptive operation decision-making mechanism for coupling and nesting of time scales. It is aimed at the change of time scale and the dynamics in the operation process, considering the relationship between...
A vehicle–track system finite element (FE) model coupled with a rail surface wear model and an offline rail profile update strategy have been developed to study the formation and evolution of rail corrugation at rail welded joints under multipl...
To address significant photovoltaic (PV) power fluctuations, large forecast errors, and differences in the operating states of battery energy storage system (BESS) units under highly variable weather conditions, this study proposes an adaptive coordi...
In view of the frequency regulation (FR) policy in Northeast China, a two-stage real-time rolling optimization model for power plants participating in FR ancillary services is established. The optimization object of the first stage is to maximize the...
To mitigate the impact of inaccurate forecasts of electric vehicle charging load and photovoltaic power generation on the operation of PV–storage–charging systems, a risk-aware adaptive conformal rolling-horizon scheduling method is propo...
A dynamic stratified classification clustering strategy is proposed to improve the precision and efficiency of clustering flexible resources in building complexes for multi-interaction scenarios, including frequency regulation, peak shaving, voltage...
Municipal solid waste incineration (MSWI) is essential for tackling urban environmental challenges and facilitating renewable energy recycling. The MSWI process has characteristics of multiple variables, strong coupling, and complex nonlinearity, req...
Complex dynamical systems are characterized by inherent nonlinearity, high dimensionality, spatiotemporal uncertainty, and implicit symmetry, posing fundamental challenges for their mathematical modeling and multi-step evolution prediction. For examp...
This paper presents the development of two adaptive autopilots for the Cessna Citation X business jet aircraft. The two adaptive control strategies, including a dynamic inversion controller and a neural network controller, provide dual adaptation. Th...
This study focuses on a large rubber-tired gantry crane (RTGC) operating in a nomadic prefabricated beam yard and develops a Digital Twin-driven dynamic feasible route planning method for the path planning problem under the combined effects of a disc...
This paper presents a target tracking algorithm based on 4D millimeter-wave radar point cloud information for autonomous driving applications, which addresses the limitations of traditional 2 + 1D radar systems by using higher resolution target point...
The integration of high-penetration renewable energy sources (RESs) and electric vehicles (EVs) increases the risk of voltage fluctuations in distribution networks. Traditional static partitioning strategies struggle to handle the intermittency of wi...
This article presents a hybrid backstepping consisting of two robust controllers utilizing the approximation property of a radial basis function neural network (RBFNN) for a quadrotor with time-varying uncertainties. The quadrotor dynamic system is d...
The control and adjustment of in-flight attitudes are critical to enlarging the flight distance of ski jumping. As one of the most important gears, the skis provide sufficient lift and drag forces for the athletes, and thus their in-flight attitudes...
The suspension system of the Electromagnetic Suspension (EMS) maglev train is crucial for ensuring safe operation. This article focuses on data-driven modeling and control optimization of the suspension system. By the Extended Dynamic Mode Decomposit...
Floating offshore wind turbines (FOWTs) experience unbalanced loads and platform motion due to the coupling of variable wind and wave loads, which leads to output power fluctuation and increased fatigue loads. This paper introduces a new blade pitch...
A CFD-based constrained three-component aerodynamic-trim procedure is implemented to investigate the load balance and coupled flowfield response of a simplified shipborne helicopter hovering over a flight deck. During the unsteady CFD calculation, th...
This paper presents a Kalman filter-based attitude estimation algorithm using a single body-mounted inertial sensor consisting of a triaxial accelerometer and triaxial gyroscope. The proposed algorithm has been developed for attitude estimation durin...
The existing multi-satellite dynamic mission planning system hardly satisfies the requirements of fast response time and high mission benefit in highly dynamic situations. In the meantime, a reasonable decision-maker preference mechanism is an additi...
Accurate prediction of fuel consumption is critical for achieving efficient and low-carbon ship operations. However, the variability of the marine environment introduces significant challenges, as it leads to dynamic changes in monitoring data, compl...
The efficient scheduling of airport logistics vehicles is crucial for ensuring timely and cost-effective ground operations, particularly under dynamic disturbances such as flight delays, cancellations, and new task arrivals. With the increasing deplo...
This paper presents a multi-state adaptive early warning method for mechanical equipment and proposes an adaptive dynamic update model of the equipment alarm threshold based on a similar proportion and state probability model. Based on the similarity...
The narrow tilting vehicle receives extensive public attention because of traffic congestion and environmental pollution, and the active rolling motion control is a traffic safety precaution that reduces the rollover risk caused by the structure size...
With the continuous development of semiconductor manufacturing technology and information technology, the sizes of wafer chips are becoming smaller and the variety is increasing, which has put forward high requirements for wafer chip precision manufa...
Federated learning enables collaborative model training across distributed devices while preserving data privacy. However, in real-world environments such as smart cities, heterogeneous and resource-constrained edge devices often render existing meth...
Background: Green logistics requires decision-support approaches that jointly address cost efficiency, emissions reduction, service reliability, and reporting transparency under dynamic operating conditions. Existing studies often treat optimization,...
As edge computing environments become increasingly dynamic, the need for efficient job scheduling and proactive fault prevention is becoming paramount. In such environments, minimizing machine downtime and maintaining productivity are critical challe...
This study addresses the insufficient representation of moving ground targets in conventional UAV air–ground risk assessment, which typically relies on static population distributions or instantaneous target locations and therefore fails to cap...
In this work, the position and attitude tracking finite-time adaptive control problem of a type of vertical take-off and landing (VTOL) aircraft system is studied. Here, the dynamic of the VTOL aircraft is subjected to external disturbances and unkno...
Model predictive control, without strict constraints on the control model, effectively overcomes problems, such as poor system dynamic quality caused by time delay, can improve control accuracy to a certain extent, and can directly process input and...
Gas well production prediction is an important means to determine the economic benefits of gas field development, and it is the key to realize the optimization of gas well production. However, with the continuous development of gas fields, the increa...
When addressing high-dimensional complex optimization problems, the vanilla Dung Beetle Optimizer (DBO) suffers from slow convergence, frequent stagnation in local optima, and progressive degradation of population diversity. To overcome the above inh...
A macro network loading model for multi-flow lines, time varying, and pedestrian congestion is proposed. The station hub is abstracted as a network of different types of nodes, and the flow of passengers at each node is calculated in real time for th...
This study presents a novel approach to a mixed-integer linear programming (MILP) model for periodic inventory management that combines reinforcement learning algorithms. The rolling horizon method (RHM) is a multi-period optimization approach that i...
This paper addresses the core issues of slow coverage rate growth and high repeated detection rates in multi-UAV cooperative search operations within unknown areas. A distributed cooperative search algorithm based on the maximum entropy mechanism is...
With rising renewable energy penetration, wind–hydrogen coupling systems are key to large-scale green hydrogen production and wind power integration. This paper proposes a multi-timescale power allocation measure and evaluation framework that e...
This paper presents an integrated active obstacle avoidance controller in the Model Predictive Control (MPC) framework to ensure adaptive collision-free obstacle avoidance under complex scenarios while maintaining a good level of vehicle stability an...
Large infrastructure projects frequently experience schedule slippage and cost escalation; however, time–cost planning still relies on expert-assigned activity parameters that fail to reflect the variability induced by construction modes, resou...
The accurate estimation of the state of charge (SOC) for lithium-ion batteries’ performance prediction and durability evaluation is of paramount importance, which is significant to ensure reliability and stability for electric vehicles. The SOC...
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