Search Results (56)

This paper addresses the insufficient speed control accuracy observed in traditional seeding systems. This paper proposes an electric drive seeding control method that incorporates a composite control strategy combining the Rime optimization algorithm (RIME) with a backpropagation neural network (BPNN). Firstly, the architecture including radar/proximity switch dual-mode speed measurement, STM32F103 main control, and asymmetric half-bridge drive was constructed. Based on the kinematic model, a motor speed-plant spacing mapping relationship was derived to complete the selection of a brushless DC motor. Secondly, this study addresses the issues of large overshoot in traditional PID control, response lag in fuzzy PID, and local optima in BP-PID. To overcome these challenges, the RIME algorithm is employed to optimize the weight-updating mechanism of the backpropagation neural network (BPNN). The soft RIME search facilitates multi-directional exploration, while the hard RIME puncture enhances global optimization capability, significantly improving the adaptive accuracy of the parameters. The simulation results showed that the adjustment time of the proposed RIME-BP-PID in the step response is 73.8% shorter than the BP-PID, and the overshoot is reduced to 0.23%. The square wave tracking error is 27.8% of the traditional PID. The bench test was carried out at 6–12 km/h speed and 200–300 mm. The results showed that, compared with BP-PID, the qualified index of RIME-BP-PID increased by 1.67–1.94 percentage points, the missed seeding index decreased by 1.25–1.80 percentage points, and the coefficient of variation decreased by 4.90–5.82 percentage points. The algorithm effectively solves the problem of the strong nonlinear time-varying control of a seeding system and provides theoretical support for the research and development of precision agricultural equipment. Full article

Thermally driven heat pumps primarily use thermal energy to drive a compression cycle. The thermal energy can be waste heat, natural-gas combustion, or solar, helping increase efficiency and reduce greenhouse-gas emissions. We study a thermal compressor heat pump (TCHP) in which Stirling-type thermal compressors (TCs) are heat-driven rather than electrically driven, delivering a nominal heat capacity of 8 kW with CO₂ as the refrigerant. Unlike most existing dynamic models of CO₂ cycles, which focus on electrically driven or single-stage systems, this work targets a heat-driven multi-stage configuration and includes transient validation. Like any vapor compression cycle (VCC), a TCHP requires a dynamic model for control and optimization; its predictive reliability must be validated on experimental data. We therefore describe the test bench and performance expressions, collect steady-state and transient datasets, and derive a hybrid dynamic model: finite-volume (FV) differential equations for slow components and quasi-static submodels (linear regressions and correlations) for fast elements. The contribution of this work is the development and experimental validation of a hybrid FV model for a multi-stage heat-driven CO₂ TCHP. Validation against both steady-state and transient datasets shows good agreement. On 15 steady-state operating points, the model reproduces pressures within ∼1 bar mean absolute error (MAE) and system-level performance (total recovered heat, $CO{P}_{\mathrm{th}}$) within ∼6% mean absolute percentage error (MAPE), with $R^2\gtrsim 0.8$; component heat-rate predictions are within ∼20% MAPE. Under transient step tests on expansion valve openings and burner fan speed, the thermal COP and total recovered heat track within $4\%$ MAPE (up to $R^2=0.96$), pressures within $1.5$ bar MAE, and the evaporator heat rate within 14–$22\%$ MAPE. Full article

This study presents the development and experimental validation of a novel wind turbine emulator (WTE) based on a doubly fed induction generator (DFIG). The proposed architecture employs an induction motor (IM) driven by a variable frequency drive (VFD) to emulate wind turbine dynamics, offering a cost-effective and low-maintenance alternative to traditional DC motor-based systems. The contribution of this work lies, therefore, not in the hardware topology itself, but in the complete real-time software implementation of the control system using C language and RTLib, which enables higher sampling rates, faster PWM updates, and improved execution reliability compared with standard Simulink/RTI approaches. The proposed control structure integrates tip–speed ratio (TSR)-based maximum power point tracking (MPPT) with flux-oriented vector control of the DFIG, fully coded in C to provide optimized real-time performance. Experimental results confirm the emulator’s ability to accurately replicate real wind turbine behavior under varying wind conditions. The test bench demonstrates fast dynamic response, with rotor currents settling in 11–18 ms, and active/reactive powers stabilizing within 25–30 ms. Overshoots remain below 10%, and steady-state errors are limited to ±1 A for currents and ±100 W/±50 VAR for powers, ensuring precise power regulation. The speed tracking error is approximately 0.61 rad/s, validating the system’s ability to follow dynamic references with high accuracy. Additionally, effective decoupling between active and reactive loops is achieved, with minimal cross-coupling during step changes. Full article

With the comprehensive digitalization and electrification of aircraft, electromechanical actuation systems (EAS) have been increasingly applied. However, EAS are affected by various nonlinear factors, such as friction and mechanical backlash, which can compromise system stability and control accuracy, thereby reducing the operational lifespan of the EAS. This study focuses on these two nonlinear factors and proposes a hybrid control approach to mitigate their effects. In the speed loop of the EAS, a Super-Twisting sliding mode controller combined with a generalized proportional–integral observer (GPIO) is designed, while in the position loop, a hybrid controller integrating a radial basis function (RBF) neural network with sliding mode control is implemented. Leveraging the advantages of numerical analysis in SIMULINK and dynamic simulation in ADAMS, a co-simulation framework is established to evaluate the hybrid control algorithm under nonlinear effects. Furthermore, a control test bench for the control surface transmission system is constructed to analyze the dynamic and static performance of the system under different control strategies and input commands. The experimental results show that, compared with the PID control, the hybrid control method reduces the steady-state error and vibration amplitude of the step response displacement by 51% and 75%, respectively, and decreases the amplitude of speed fluctuations by 75%. For the sinusoidal response, the displacement lag is reduced by 76%, and the amplitude of speed fluctuations is reduced by 50%. Full article

This paper presents an integrated downhole risk prevention and control system designed to enhance safety, efficiency and sustainability in deep-well drilling operations. The system incorporates advanced measurement processing, risk evaluation, and intelligent data transmission technologies for real-time monitoring of nine key drilling parameters, such as downhole drilling pressure, bending moment, and torque, etc. Bench tests and field trials demonstrated the system’s reliability in accurately capturing and transmitting data under high-pressure, high-temperature conditions. For instance, it successfully monitored bottom-hole pressure up to 61.4 MPa and temperature to 120.8 °C, allowing for early detection of abnormal events such as pressure kicks and torsional stick-slip. The system was laboratory-tested to withstand bottom-hole pressures up to 61.4 MPa and temperatures of 120.8 °C. During field trials, the tool operated safely under actual downhole conditions of approximately 59.2 MPa and 115 °C, which are within its rated limits. The system also facilitated automated controlled actions, including mud weight and pump rate control, to prevent incidents. These results underscore the system’s potential to significantly improve real-time and intelligent process control, minimize operational risks, and advancing the sustainability of drilling practices. The approach marks a step forward in intelligent drilling technologies, supporting proactive decision-making in energy extraction. Future work will extend this system to ultra-deep and high-temperature wells while integrating advanced AI-based analytics for further optimization. Full article

Aiming to solve the difficult problem of the miniaturization of servo valves, this paper designs a subminiature two-dimensional (2D) electro-hydraulic servo valve, which realizes the integration of the pilot stage and the power stage and significantly improves the work-to-weight ratio. Meanwhile, a high-power-density brushless DC motor (BLDC) is adopted as the electro-mechanical converter to further reduce the volume and mass. Firstly, the structure and working principle of the two-dimensional (2D) servo valve are described, and the mathematical model of the electro-mechanical converter is established. Aiming at the special working condition of the electro-mechanical converter with high-frequency oscillation at a small turning angle, this paper designs a position–current double closed-loop PID control algorithm based on the framework of the vector control algorithm (FOC). At the same time, the current feedforward compensation technique is included to cope with the high-frequency nonlinear disturbance problem of the electro-mechanical converter. The stability conditions of the electro-mechanical converter and the main valve were established based on the Routh–Hurwitz criterion, and the effects of the control algorithm of the electro-mechanical converter and the main parameters of the main valve on the stability of the system were analyzed. The dynamic and static characteristics of the 2D valve were simulated and analyzed by establishing a joint simulation model in Matlab/Simulink and AMESim. The prototype was fabricated, and the experimental bench was built; the size of the experimental prototype was 31.7 mm × 29.3 mm × 31 mm, and its mass was 73 g. Under a system pressure of 7 MPa, the flow rate of this valve was 5 L/min; the hysteresis loop of the spool-displacement input–output curve was 4.8%, and the linearity was 2.54%, which indicated that it had the ability of high-precision control and that it was suitable for the precision fluid system. The step response time was 7.5 ms, with no overshoot; the frequency response amplitude bandwidth was about 90 Hz (−3 dB); the phase bandwidth was about 95 Hz (−90°); and the dynamic characterization experiment showed that it had a fast response characteristic, which can satisfy the demand of high-frequency and high-dynamic working conditions. Full article

Focusing on an energy-saving winch-type heave compensation system applicable to real working conditions, with the objective of enhancing compensation accuracy, a wavelet neural network was employed for platform velocity prediction, and the prediction results were applied to velocity disturbance compensation control. Initially, the ITTC two-parameter spectrum was utilized to generate wave spectral diagrams under different sea conditions, along with displacement and velocity data of the floating platform’s heave motion. Subsequently, a time-series-based wavelet neural network velocity prediction model was developed, trained, and tested. Comparative analyses were performed on prediction performance differences across varying prediction steps and sea condition levels. Then, the effectiveness of the time-series-based wavelet neural network prediction model was validated through a valve-controlled hydraulic cylinder heave motion simulation system. Experimental results indicated that the wavelet neural network-based velocity prediction method effectively improved the compensation accuracy of the winch-type heave compensation system. Finally, after verifying the effectiveness of the wavelet neural network prediction model based on time series, the compensation performance of the system after adding the velocity prediction module was tested and verified using the winch-type heave compensation simulation test bench built by the research team. After experimental verification, after adding velocity prediction, the compensation accuracy of the system was improved by 19% compared with that without velocity prediction. Full article

With the continuous development of industrial automation, diesel engines play an increasingly important role in various types of construction machinery and power generation equipment. Improving the dynamic and static performance of the speed control system of single-cylinder diesel engines can not only significantly improve the efficiency of the equipment, but also effectively reduce energy consumption and emissions. Particle swarm optimization (PSO) fuzzy PID control algorithms have been widely used in many complex engineering problems due to their powerful global optimization capability and excellent adaptability. Currently, PSO-based fuzzy PID control research mainly integrates hybrid algorithmic strategies to avoid the local optimum problem, and lacks optimization of the dynamic noise suppression of the input error and the rate of change of the error. This makes the algorithm susceptible to the coupling of the system uncertainty and measurement disturbances during the parameter optimization process, leading to performance degradation. For this reason, this study proposes a new framework based on the synergistic optimization of the untraceable Kalman filter (UKF) and PSO fuzzy PID control for the speed control system of a single-cylinder diesel engine. A PSO-optimized fuzzy PID controller is designed by obtaining accurate speed estimation data using the UKF. The PSO is capable of quickly adjusting the fuzzy PID parameters so as to effectively alleviate the nonlinearity and uncertainty problems during the operation of diesel engines. By establishing a Matlab/Simulink simulation model, the diesel engine speed step response experiments (i.e., startup experiments) and load mutation experiments were carried out, and the measurement noise and process noise were imposed. The simulation results show that the optimized diesel engine speed control system is able to reduce the overshoot by 76%, shorten the regulation time by 58%, and improve the noise reduction by 25% compared with the conventional PID control. Compared with the PSO fuzzy PID control algorithm without UKF noise reduction, the optimized scheme reduces the overshoot by 20%, shortens the regulation time by 48%, and improves the noise reduction effect by 23%. The results show that the PSO fuzzy PID control method with integrated UKF has superior control performance in terms of system stability and accuracy. The algorithm significantly improves the responsiveness and stability of diesel engine speed, achieves better control effect in the optimization of diesel engine speed control, and provides a useful reference for the optimization of other diesel engine control systems. In addition, this study establishes the GT-POWER model of a 168 F single-cylinder diesel engine, and compares the cylinder pressure and fuel consumption under four operating conditions through bench tests to ensure the physical reasonableness of the kinetic input parameters and avoid algorithmic optimization on the distorted front-end model. Full article

Environmental DNA from bulk materials can be analyzed to gain an understanding of the bacterial, fungal, plant, and/or arthropod communities present. DNA metabarcoding is widely used to characterize these biological communities, by amplifying “barcode” regions and sequencing these amplicons via next-generation sequencing. The Earth Microbiome Project (EMP) adopted the use of indexed primers, PCR primers containing Illumina^® adapter sequences and a unique 12-nucleotide Golay barcode to simplify the identification of bacterial taxa via the 16S barcode. We sought to develop a wet laboratory workflow utilizing indexed primers that could cost-effectively reduce bench time while simultaneously targeting multiple DNA barcode regions to characterize bacterial (16S), fungal (ITS1), plant (ITS2, trnL p6 loop), and arthropod (COI) communities. The EMP primer constructs for 16S were modified to accommodate our DNA barcode regions of interest while also permitting successful demultiplexing following sequencing. A single indexed primer pair was designed for ITS1 and trnL p6 loop, and two primer pairs were developed for ITS2 and COI. To test the workflow, a total of 648 soil and 336 dust samples were processed, with key steps including DNA isolation, total DNA quantification, amplification with indexed primers, library purification and quantification, and Illumina MiSeq sequencing. Based on raw read counts and analysis of positive controls, the trnL p6 loop and ITS2 a primer pairs performed comparably to the originally designed 16S primers. Both COI primers pairs, ITS1 and ITS2 b primers, had lower raw reads compared to the other three primer pairs. The combination of the three plant targets successfully recovered all plant taxa in the positive controls except for Nephrolepis exaltata [Nephrolepidaceae] and the COI primers recovered all arthropod taxa except for the beetle. Notably, none of the taxa in the fungal positive control were recovered using ITS1. For environmental samples, sequencing was successful for all primers except COI c, and primer biases were observed for all three plant primers, in which a small number of families were uniquely amplified for each primer pair. This workflow can be applied to many disciplines that utilize DNA metabarcoding given its customizability and flexibility with Illumina sequencing chemistry. Full article

The high prevalence of conditions leading to foot drop highlights the need for devices that restore functionality, enabling patients to regain a natural gait pattern. There is a demand for a portable, lightweight, low-cost, and efficient active ankle-foot orthosis. In this work, we present the prototype of a new design that was simulated in a previous contribution, with a test bench evaluation of the low-level control. The dynamical behavior of a cam suspension interaction with a proportional–integral–derivative controller system for transmission is evaluated. The proposed active orthosis includes a novel cam-based actuator, designed to intervene at the dorsiflexion stage of gait, without influencing the plantar flexion. This design is aimed at specific lower limb ailments that cause a need for assistance only in raising the foot, and it leverages a commercial servomotor to achieve ankle angle tracking. System identification was performed using a test bench, with three degrees of freedom to emulate tibial motion during gait. Response evaluations of the device showed low values for the integral time squared error, peak overshoot, and settling time for step inputs, with and without additional periodic perturbations. The root mean squared error of the device while tracking an ankle angle signal varied from 0.1 to 6.5 degrees, depending on the speed of the changes. Full article

To address the issues of poor positioning accuracy, low supply efficiency and inadequate adaptability for different tray specifications of the existing seedling tray conveying device, a dual-axis positioning tray conveying device was developed, which can accommodate seedling trays ranging from 21 to 288 holes. A dual-sensor positioning algorithm and variable displacement positioning method were proposed to increase the efficiency, ensuring precise initial positioning and intermittent movements both along the seedling conveyance (X-axis) and platform movement (Y-axis). The system utilizes a precise positioning servo-control system with three-closed-loop controls and a PID algorithm enhanced through simulation to refine seedling positioning accuracy. Experiments with nine different tray specifications were conducted on a step-controlled platform to test suitability, validating the performance of the initial positioning and intermittent transport in both the X and Y directions. On the X-axis, the initial positioning deviation of the seedling tray was up to 1.34 mm and the maximum deviation in the intermission conveying was 0.85 mm. Comparatively, the deviation on the Y-axis was smaller, with the initial positioning deviation up to 0.99 mm and the intermission moving deviation up to 0.98 mm. These results demonstrate that the designed device meets the requirements for precise transport, providing essential technological foundations for seedling tray transport and retrieval steps in fully automated transplanting machines. Full article

Sensors based on MEMS technology, in particular Inertial Measurement Units (IMUs), when installed on vehicles, provide a real-time full estimation of vehicles’ state vector (e.g., position, velocity, yaw angle, angular rate, acceleration), which is required for the planning and control of cars’ trajectories, as well as managing the in-car local navigation and positioning tasks. Moreover, data provided by the IMUs, integrated with the data of multiple inputs from other sensing systems (such as Lidar, cameras, and GPS) within the vehicle, and with the surrounding information exchanged in real time (vehicle to vehicle, vehicle to infrastructure, or vehicle to other entities), can be exploited to actualize the full implementation of “smart mobility” on a large scale. On the other hand, “smart mobility” (which is expected to improve road safety, reduce traffic congestion and environmental burden, and enhance the sustainability of mobility as a whole), to be safe and functional on a large scale, should be supported by highly accurate and trustworthy technologies based on precise and reliable sensors and systems. It is known that the accuracy and precision of data supplied by appropriately in-lab-calibrated IMUs (with respect to the primary or secondary standard in order to provide traceability to the International System of Units) allow guaranteeing high quality, reliable information managed by processing systems, since they are reproducible, repeatable, and traceable. In this work, the effective responsiveness and the related precision of digital IMUs, under sinusoidal linear and curvilinear motion conditions at 5 Hz, 10 Hz, and 20 Hz, are investigated on the basis of metrological approaches in laboratory standard conditions only. As a first step, in-lab calibrations allow one to reduce the variables of uncontrolled boundary conditions (e.g., occurring in vehicles in on-site tests) in order to identify the IMUs’ sensitivity in a stable and reproducible environment. For this purpose, a new calibration system, based on an oscillating rotating table was developed to reproduce the dynamic conditions of use in the field, and the results are compared with calibration data obtained on linear calibration benches. Full article

Due to the increasing complexity of vehicle software, it is becoming increasingly difficult to comprehensively test all requirements. This inevitably means that alternative test methods, e.g., simulation-based methods, must be used more frequently. However, the challenge involves identifying appropriate requirements that can be technically tested in a simulation environment initially. The present work is aimed at evaluation and optimization of the effectiveness of software-in-the-loop (SiL) simulations in the testing process of vehicle software. The focus is on supporting the testing process by shifting specific test cases from hardware-in-the-loop (HiL) test benches to SiL-based simulations. For this purpose, a systematic approach was developed to analyze and categorize requirements, enabling precise and efficient allocation of test cases. Furthermore, a detailed review and recommendation for improving the ProSTEP iViP standard for virtual electronic control units (vECU) was carried out. The developed matrix associates the defined requirement clusters with different classifications of vECUs, facilitating the identification of suitable test environment types for conducting specific test cases. By assigning test cases to appropriate vECU levels, the testing processes can be targeted and cost-optimized. Finally, the theoretical results were evaluated in an SiL simulation environment. It was observed that a significant part of the requirements could effectively be tested using a vECU. These findings confirmed the potential of SiL simulation environments to not only support, but also enhance, the testing process for vehicle software by providing a cost-effective and flexible complement to traditional HiL test benches. Full article

To explore the solution of the two-step method applied in the rapid construction of super large cross-section tunnels passing through IV-and V-grade surrounding rock sections in karst cave areas, based on an engineering example of the Lianhuashan Tunnel, we use the numerical calculation method to analyze the stability of surrounding rock and the design parameters of the control measures for super large cross-section tunnels during the construction of the step method. The calculated results show that the working face of IV-grade surrounding rock can be stabilized by an advanced small pipe, and the stability of the supporting structure should be controlled mainly by IV-grade surrounding rock. In order to control the stability of the tunnel face, it is necessary to use an advanced large pipe shed in the surrounding V-grade rock. The reinforcement range of the advanced large pipe shed is 120° and the length is 20 m. This is the most economical design parameter of the advanced large pipe shed, ensuring the deformation control effect. For control of the stability of the supporting structure, under the condition that the working space is suitable for large machinery, the settlement of the arch of the supporting structure can be obviously reduced by shortening the step cycle footage and reducing the step length, and the peripheral convergence of the supporting structure can be obviously reduced by reducing the step height. After comprehensive analysis and considering the development of karst caves, the advanced support measures, design parameters, bench excavation design parameters, initial support measures, karst cave treatment measures, and bench construction process of IV- and V-grade surrounding rock is determined. The application verification shows that the research results have a good control effect on the stability of the surrounding rock and cave and are suitable for large-scale mechanical operations, which can significantly improve the excavation speed of the super large cross-section tunnel passing through the IV- and V-grade surrounding rock sections in the karst cave area. Full article

An electrified vehicle equipped with a stepped-ratio transmission and clutch(es) requires precise control of the clutch actuator(s) and power sources to achieve optimal gear shift performance, which is characterized by smooth and swift gear shifts. Owing to the absence of the smoothing effect of torque converters, dual-clutch transmission (DCT) powertrains are prone to inducing abrupt shift shocks—particularly during rapid clutch-to-clutch shifts. Balancing the smoothness and speed of shifts is a significant challenge and was the key focus of this study. Multiple experiments and model-based analyses were conducted to investigate the tradeoff between smoothness and shift time during the clutch-to-clutch shifts of a parallel-type hybrid electric vehicle with a dry DCT. Additionally, the adverse effects of inaccurate power-source control on shift quality were experimentally investigated. The results revealed the primary physical factors in terms of control causing torsional driveline oscillations in clutch-to-clutch shifts. According to these observations, a detailed quantitative guide including how to generate reference trajectories for shift control is proposed, with the aim of reducing the driveline torsional vibrations without compromising the shift time. The effectiveness of the proposed control strategy was demonstrated through real-time experiments on an electrified powertrain with a DCT using a dedicated test bench. This study provides valuable insights for optimizing the shift performance of electrified vehicles—particularly for managing torsional vibrations during clutch-to-clutch shifts. Full article