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Taking a direct-drive volume control (DDVC) electro-hydraulic servo system as the research object and aiming at the problems of the servo motor torque fluctuation, high-precision system pressure control, and dynamic response of the system, based on traditional motor direct torque control (DTC), a motor direct torque control method based on a sliding-mode variable structure is proposed to control the system pressure. The motor torque loop is part of the inner control loop and has a rapid dynamic response speed, resulting in higher pressure control accuracy. A nonlinear mathematical model was established for the DDVC electro-hydraulic servo system. The switch meter hysteresis controller in the traditional DTC system was replaced with space vector pulse-width modulation technology. Then, the PID control module in space vector modulation technology was replaced with high-order sliding-mode variable-structure control. Through the coupling relationship between the electric machine and the constant-displacement pump, the pressure can be controlled with high precision using motor torque control. Finally, using the MATLAB/Simulink simulation platform and the DDVC electro-hydraulic servo system simulation model, the proposed theoretical approach to torque control was verified on the basis of simulations and experiments, and the performance with regard to pressure control in the hydraulic system was observed. The simulation and experimental results show that the designed torque control is able to effectively reduce the motor torque fluctuation and improve the dynamic response characteristics of the system. The system pressure control is superior to traditional pressure control methods based on speed regulation, and it has higher control accuracy and a better dynamic response.

A system for the rapid prototyping of real-time control algorithms for open-circuit variable displacement axial-piston pumps is presented. In order to establish real-time control, and communication and synchronization with the programmable logic controller of an axial piston pump, the custom CAN communication protocol is developed. This protocol is realized as a Simulink® S-function, which is a part of main Simulink® model. This model works in real-time and allows for the implementation of rapid prototyping of various control strategies including advanced algorithms such as H∞ control. The aim of the algorithm is to achieve control system performance in the presence of various load disturbances with an admissible control signal rate and amplitude. In contrast to conventional systems, the developed solution suggests using an embedded approach for the prototyping of various algorithms. The obtained results show the advantages of the designed H∞ controller that ensure the robustness of a closed-loop system in the presence of significant load disturbances. These type of systems with displacement volume regulation are important for industrial hydraulic drive systems with relatively high power.

Recently, wind farms consisting of clusters of closely spaced vertical-axis wind turbines (VAWTs) have attracted the interest of many people. In this study, a method using a wake model to predict the flow field and the output power of each rotor in a VAWT cluster is proposed. The method uses the information obtained by the preliminary computational fluid dynamics (CFD) targeting an isolated single two-dimensional (2D) VAWT rotor and a few layouts of the paired 2D rotors. In the method, the resultant rotor and flow conditions are determined so as to satisfy the momentum balance in the main wind direction. The pressure loss of the control volume (CV) is given by an interaction model which modifies the prepared information on a single rotor case and assumes the dependence on the inter-rotor distance and the induced velocity. The interaction model consists of four equations depending on the typical four-type layouts of selected two rotors. To obtain the appropriate circulation of each rotor, the searching range of the circulation is limited according to the distribution of other rotors around the rotor at issue. The method can predict the rotor powers in a 2D-VAWT cluster including a few rotors in an incomparably shorter time than the CFD analysis using a dynamic model.

We present PLC-based fractional-order controller design for an industrial-oriented water tank volume control application. The system comprises input delay which is a typified characteristic in such industrial process control applications. The particular contribution of this work is on discrete fractional-order PID implementation via PLC and its application to the aforementioned realistic water tank test bed. Stability and robustness properties of fractional-order discrete PID feedback-loops for different approximation methods and orders are also shown. Fractional-order controllers are obtained for a variety of stability margin choices, and benefits of the non-integer-order controllers compared to the integer-order PID control are illustrated via simulation and experimental runs on a realistic test-bed.

To address the challenge of intelligently controlling air volume in regions affected by the frequent fluctuations in underground ventilation networks, a remote intelligent air regulation method based on machine learning was presented. This method encompasses three core components: local fan frequency conversion regulation, associated branch air resistance regulation, and a comprehensive integration of both. Leveraging foundational mine ventilation theory, the principles behind branch sensitivity air regulation were dissected. By applying these principles, the key performance indicators crucial for the regulation of air volume within the ventilation system were identified. Subsequently, an intelligent model for regional air volume control was constructed. To validate the approach, an experimental platform for intelligent air volume control was established, guided by geometric, dynamic, and kinematic similarity criteria. Then, the experimental methodologies for simulating various ventilation scenarios were discussed, the data acquisition techniques were introduced, and the obtained results were analyzed. Employing machine learning techniques, we utilized five distinct algorithms to predict the operational parameters of targeted air volume ventilation equipment. It enabled precise and efficient control of air volume within the region. The results indicated that the least squares support vector machine (LS-SVM) stood out by delivering high-precision predictions of target air volume ventilation equipment parameters, all while maintaining a relatively short calculation time. This swift generation of feedback data and corresponding air volume control strategies will contribute to the precise management of air volume in the area. This work served as a valuable theoretical and practical guide for intelligent mining ventilation control.

Classical relationships between cumulative and maximum seismic moment, based on the Gutenberg‐Richter law, shows a non‐physical anomaly for low b‐values. We here derive new relationships, including a low and a high b‐value approximation. We apply these theoretical relationships to a comprehensive set of 17 induced seismic sequences, by examining the growth of the released seismicity with the injected volume. While the event number is found to be directly proportional to the volume, the cumulative and maximum seismic moment depends on the volume with an exponent that depends at first order on the b‐value. This is confirmed by the theoretical relationships we derived, and shows that the injected volume primarily controls seismic nucleation and therefore the seismic rate of occurrence. The magnitude dependence on b‐value, which is not considered in most moment‐volume relationships, may have a significant impact on earthquake magnitude forecasting for monitoring purposes.

The study aims to enhance the machining accuracy and reduce the energy consumption of a computer numerical control (CNC) machine. A multiobject cooling control system was devised that can effectively remove the generated heat of two operational spindles in parallel arrangement by employing a varied coolant volume control method. In the multiobject cooling system, the openings of the two-way valves in front of the spindles under different spindle rotating speeds could be adjusted to maintain a constant coolant temperature difference of 3.5 °C ± 0.1 °C between the inlet and the outlet of the spindles. Due to the adjustable openings of the two-way valves, the coolant pressure between the supplied coolant and return ports in the primary loop is variable. A regression equation was established for the supplied coolant volume control in terms of the coolant pressure difference in the primary coolant loop and the driving frequency of the coolant pump for different spindle cooling loads. By adjusting the driving frequency of the coolant pump in terms of the regression equation, the supplied coolant volume can be controlled with the cooling load variations under different rotating speeds of the spindles and the energy consumption of the coolant pump can be greatly reduced as well. In comparison to the traditional case of two spindles with two individual coolers using the constant coolant volume control method, the initial investment in cooling systems could be greatly reduced by the varied coolant volume control of the multiobject cooling system. The accuracy of the spindles could be improved by 5.5 to 41.7%, and the operational power consumption could be reduced by 11 to 34%, while the rotating speed of one spindle varies from 10,000 ~ 22,000 rpm, and the other spindle is 10,000 rpm. The total lifetime carbon emissions can be reduced from 72,981 to 52,595.5 kg under different spindle rotating speeds, and the initial capital cost can be reduced from 8832 to 4729 USD. By using the multiobject cooling system for the two-spindle system, the initial capital cost can be reduced by 46.5%.

Wearable sensors to continuously measure blood pressure and derived cardiovascular variables have the potential to revolutionize patient monitoring. Current wearable methods analyzing time components (e.g., pulse transit time) still lack clinical accuracy, whereas existing technologies for direct blood pressure measurement are too bulky. Here we present an innovative art of continuous noninvasive hemodynamic monitoring (CNAP2GO). It directly measures blood pressure by using a volume control technique and could be used for small wearable sensors integrated in a finger-ring. As a software prototype, CNAP2GO showed excellent blood pressure measurement performance in comparison with invasive reference measurements in 46 patients having surgery. The resulting pulsatile blood pressure signal carries information to derive cardiac output and other hemodynamic variables. We show that CNAP2GO can self-calibrate and be miniaturized for wearable approaches. CNAP2GO potentially constitutes the breakthrough for wearable sensors for blood pressure and flow monitoring in both ambulatory and in-hospital clinical settings. Realizing wearable sensors for blood pressure (BP) monitoring with clinically-acceptable performance remains a significant challenge. Here, the authors report a continuous noninvasive blood pressure measurement system featuring a volume control technique for small wearable sensors.

Mitochondria and the complex endomembrane system are hallmarks of eukaryotic cells. To date, it has been difficult to manipulate organelle structures within single live cells. We developed a FluidFM-based approach to extract, inject, and transplant organelles from and into living cells with subcellular spatial resolution. The technology combines atomic force microscopy, optical microscopy, and nanofluidics to achieve force and volume control with real-time inspection. We developed dedicated probes that allow minimally invasive entry into cells and optimized fluid flow to extract specific organelles. When extracting single or a defined number of mitochondria, their morphology transforms into a pearls-on-a-string phenotype due to locally applied fluidic forces. We show that the induced transition is calcium independent and results in isolated, intact mitochondria. Upon cell-to-cell transplantation, the transferred mitochondria fuse to the host cells mitochondrial network. Transplantation of healthy and drug-impaired mitochondria into primary keratinocytes allowed monitoring of mitochondrial subpopulation rescue. Fusion with the mitochondrial network of recipient cells occurred 20 minutes after transplantation and continued for over 16 hours. After transfer of mitochondria and cell propagation over generations, donor mitochondrial DNA (mtDNA) was replicated in recipient cells without the need for selection pressure. The approach opens new prospects for the study of organelle physiology and homeostasis, but also for therapy, mechanobiology, and synthetic biology.

The multiaxial fatigue strength of severely notched titanium grade 5 alloy (Ti-6Al-4V) is investigated. Experimental tests under combined tension and torsion loading, both in-phase and out-of-phase, have been carried out on axisymmetric V-notched specimens considering different nominal load ratios (R = -1, 0). All specimens are characterized by a notch tip radius less than 0.1 mm, a notch depth of 6 mm and a notch opening angle equal to 90 degrees. The experimental data from multiaxial tests are compared with those from pure tension and pure torsion tests on un-notched and notched specimens, carried out at load ratio ranging from R = -3 to R = 0.5. In total, more than 160 new fatigue data are examined, first in terms of nominal stress amplitudes referred to the net area and then in terms of the local strain energy density averaged over a control volume surrounding the V-notch tip. The dependence of the control radius on the loading mode is analysed showing a very different notch sensitivity for tension and torsion. For the titanium alloy Ti-6Al-4V, the control volume is found to be strongly dependent on the loading mode