Precise Control Method Research Articles

Adaptive histogram equalization framework based on new visual prior and optimization model

Histogram Equalization (HE) algorithm remains one of the research hotspots in the field of image enhancement due to its computational simplicity. Despite numerous improvements made to HE algorithms, few can comprehensively account for all major drawbacks of HE. To address this issue, this paper proposes a novel histogram equalization framework, which is an adaptive and systematic resolution. Firstly, a novel optimization mathematical model is proposed to seek the optimal controlling parameters for modifying the histogram. Additionally, a new visual prior knowledge, termed Narrow Dynamic Prior (NDP), is summarized, which describes and reveals the subjective perceptual characteristics of the Human Visual System (HVS) for some special types of images. Then, this new knowledge is organically integrated with the new model to expand the application scope of HE. Lastly, unlike common brightness preservation algorithms, a novel method for brightness estimation and precise control is proposed. Experimental results demonstrate that the proposed equalization framework significantly mitigates the major drawbacks of HE, achieving notable advancements in striking a balance between contrast, brightness and detail of the output image. Both objective evaluation metrics and subjective visual perception indicate that the proposed algorithm outperforms other excellent competition algorithms selected in this paper.

Hybrid model-based predictive HVAC control through fast prediction of transient indoor temperature fields

Efforts to reduce energy demand in the building sector have prompted a focus on the operational control of HVAC systems. Despite extensive research on HVAC control based on temperature prediction models, existing approaches often rely on node-based or average temperature predictions, which lack the detailed temperature distribution data necessary for accurate control, especially in transient situations with both spatial and temporal variations. This study introduces a precise HVAC control method based on a fast temperature field prediction model. By combining the single-step prediction response coefficient (SPRC) method with Convolutional Neural Network (CNN) architecture, sub-temperature field prediction models for multiple independent heat sources were constructed and integrated to achieve fast temperature field predictions. Subsequently, utilizing the predicted temperature field, air conditioning operation parameters were optimized and controlled to minimize energy consumption. Application of the proposed method in real building scenarios demonstrated the temperature field predictions closely aligned with computational fluid dynamics (CFD) simulations, achieving a mean absolute error (MAE) of 0.27 °C and a root mean square error (RMSE) of 0.24 °C. Furthermore, this model achieved a notable 57.8 % improvement in prediction accuracy compared to models relying solely on single-step prediction responses. Additionally, the model predictive control based on the hybrid model's temperature field predictions significantly reduced the runtime of the HVAC system by 18.18 % while maintaining temperatures within the comfort range throughout the operation period. The method presents a promising avenue for optimizing HVAC operations and minimizing energy consumption in building environments, thereby contributing to sustainable building management practices.

Tunable Mesoporous Porphyrin‐Based Conjugated Polymer Capable of Boosting Four‐Electron Zn‐I2 Batteries

AbstractPorphyrin‐based conjugated polymers (PCPs) have garnered significant attention due to their exceptional conjugated π‐electron system and remarkable physical/chemical properties, further endowing them with ordered mesoscopic architecture to break the intrinsic non/microporous restriction is highly desirable, but it still remains a great challenge. Herein, a facile bottom‐up approach for fabricating ordered mesoporous PCPs (mPCPs) with tunable mesoporous channels through colloid‐mediated self‐assembly are presented. The resultant orders mesoscopic architecture featuring a substantial specific surface area (99.3 m2 g−1) and polar skeleton, remarkably improved anchoring properties for iodine chloride molecule. Meanwhile, the optimized mass transport facilitated by the robust mesoporous channels, coupled with the increased accessibility of polar functional groups, renders the structures with an ideal nanoreactor for the highly synergistic stabilization of the four‐electron I+/I2/I− conversion process. Therefore, the mPCPs host exhibits a high specific capacity (321 mA h g−1 at 0.5 A g−1), excellent rate performance, and cycle stability (266 mAh g−1 at 3.0 A g−1 after 1800 cycles), underscoring its potential as an effective platform for zinc‐iodine batteries. This study will provide a new method for precise control and engineering of mesoporous structures tailored for specific functionalities and electrochemical requirements, thereby facilitating the development of advanced materials based on multi‐electron energy storage applications.

Research Progress on the Regulation Methods for Selective Separation and Precise Control of Two-dimensional (2D) Lamellar Membranes

Selective separation and precise control of the structure and surface characterization for two-dimensional (2D) membranes is the key technology that requires to be revealed for further development of the material in practical application. Current researches focus on the cross-linking and modification of single nanosheet to improve and manipulate the performance of 2D lamellar membranes. In this paper, the selectivity principles such as size exclusion, charge properties, and surface chemical affinity in the separation process of 2D membranes were comprehensively and systematically reviewed, as well as the preparation of hybrid membranes combining the advantages of various raw materials. We also analyzed the practical application for the separation principles in relevant researches and discussed the development directions of 2D membranes. These inductions have certain summary and guiding significance for the selective regulation and goal-oriented design of 2D membranes.

Hydrophobic iron oxide nanoparticles: Controlled synthesis and phase transfer via flash nanoprecipitation

Iron oxide nanoparticles (IONPs) synthesized via thermal decomposition find diverse applications in biomedicine owing to precise control of their physico-chemical properties. However, use in such applications requires phase transfer from organic solvent to water, which remains a bottleneck.Through the thermal decomposition of iron oleate (FeOl), we systematically investigate the impact of synthesis conditions such as oleic acid (OA) amount, temperature increase rate, dwell time, and solvent on the size, magnetic saturation, and crystallinity of IONPs. Solvent choice significantly influences these properties, manipulating which, synthesis of monodisperse IONPs within a tunable size range (10-30 nm) and magnetic properties (75 to 42 Am2Kg-1) is obtained.To enable phase transfer of IONPs, we employ flash nanoprecipitation (FNP) for the first time as a method for scalable and precise size control, demonstrating its potential over conventional methods. Poly(lactic-co-glycolic acid) (PLGA)-coated IONPs with hydrodynamic diameter (Hd) in the range of 250 nm, high colloidal stability and high IONPs loadings up to 43% were obtained, such physicochemical properties being tuned exclusively by the size and hydrophobicity of starting IONPs. They showed no discernible cytotoxicity in human dermal fibroblasts, highlighting the applicability of FNP as a novel method for the functionalization of hydrophobic IONPs for biomedicine.

Precise pose control of shaft boring machine considering the characteristic of stratum

The shaft boring machine (SBM) is innovatively applied to shaft engineering with depth and large diameter for the advantages of efficiency, adaptability, and safety. The manual and rough pose control of SBM blocks the improvement of engineering quality and efficiency. This article presents a precise pose control method for SBM considering the characteristics of strata. The kinematic model of SBM and the mechanical-hydraulic-rock coupled dynamic model of grippers actuator are established considering the characteristics of different surrounding rock, respectively. A test rig is established to validate these models. The stratum-adapted double-layer controller is designed for the pose control from the practical aspects, including the deviation and inclination of the SBM center. The upper layer devotes to the kinematic planning between pose and displacement of grippers. The linear active disturbance rejection control (LADRC) method is used to control each gripper in the lower layer. The compensation control strategy is proposed to improve the reliability of the system under the different strata conditions. The stratum-adapted property is validated with the simulation of different surrounding rock characteristics. The control test under hard rock condition is performed with the test rig. The results indicate that the displacement control error of the single gripper cylinder is less than 1.8%, and the corresponding control error of deviation and inclination angle of the SBM center is less than 2.1% and 2.3% respectively. The proposed method can cover the precise pose control under different strata conditions, and it can be applied in the shaft infrastructure construction practically.

A Precise Temperature Control Method for Lithium-ion Battery Pack based on the Nonlinear Model Predictive Control Algorithm

Abstract To utilize the maximum performance of the battery while ensuring its thermal safety, a battery thermal management system is used to control the battery maximum temperature within a safe range. This paper centres on the establishment of a temperature prediction model and the development of the nonlinear-based model predictive control (MPC) strategy. First, to address the need of predicting battery temperature, this paper develops a distributed parameter thermal resistance model to predict battery temperature quickly and accurately. Secondly, the open-loop formulation of the nonlinear-based MPC is derived based on the established state space equations. Then the soft and hard constraints of the model are established based on the actual current conditions, pump conditions, temperature difference and temperature rise indexes, so as to establish the objective function of the MPC algorithm. Finally, the established temperature nonlinear MPC algorithm is embedded on the board and the hardware platform of battery liquid cooling system is established. The experiment test result shows that the maximum error of temperature control is less than 0.1°C, and the effectiveness of the temperature control strategy of lithium-ion battery is verified through experiments.

Raman spectroscopic study of concentration dynamics in glycine crystallization achieved by optical trapping

This study investigates concentration dynamics during optical trapping-induced crystallization (OTIC) of glycine using Raman spectroscopy. In-situ Raman spectroscopy demonstrated that tightly focused laser beams induced faster concentration increase and crystal nucleation at higher supersaturation compared to loosely focused beams. Also, by varying numerical aperture (NA) values of the objective lens used, it was revealed that higher NA led to achieving a shorter induction time and higher crystallization probability. Remarkably, optical trapping using objective lenses with higher NA generated stable liquid droplets, inhibiting crystallization until considerably higher supersaturation was realized. These findings elucidate the complex interplay between optical forces, supersaturation, and crystallization dynamics on the mechanism of OTIC and offer a new method for precise control of laser-induced crystallization. We believe that the insights gained by this study pave the way for innovative developments in crystal chemistry and promising advancements in photochemistry.

Research on Precision Control and Optimization of Automatic Feeding Device of Stamping Die

This paper discusses the precision control and optimization method of automatic feeding device of stamping die. By analyzing the accuracy of the existing feeding device, the main influencing factors are identified. To solve these problems, a comprehensive scheme of structural design optimization, control system improvement and precision test method optimization is proposed. The specific research contents include the improvement of the mechanical structure of the feeding device, the application of advanced algorithms in the control system, and the improvement of precision testing equipment and methods. Through experimental verification, the optimized feeding device has been significantly improved in precision and efficiency, effectively reducing the scrap rate in production, improving the overall production efficiency and product quality, and providing important technical support for precision manufacturing in industrial production.

Precise Control and Prevention Methods for Whitefly in Greenhouse Vegetables

Trialeurodes vaporariorum Westwood (greenhouse whitefly) are worldwide polyphagous pests of economic importance that damage solanaceous vegetables. Neonicotinoid pesticides and parasitoid Encarsia formmosa Gahan are the main management strategies applied worldwide, but precise control methods in greenhouse vegetables need to be developed to reduce the application amounts of pesticides and improve the suppression of whitefly populations. Therefore, we assessed the indoor acute toxicities and risk assessment of neonicotinoids for T. vaporariorum and E. formosa adults and pupae and compared the control effects of E. formosa and neonicotinoid acetamiprid. According to the acute toxicities results, most neonicotinoid insecticides were more toxic to E. formosa than T. vaporariorum, and pupae were much less susceptible than adults of both species. Moreover, acetamiprid had a low risk effect on E. formosa. Sole application of E. formosa and acetamiprid could effectively control T. vaporariorum, but their combined application resulted in antagonistic effects on the control of T. vaporariorum. The results showed that a combined application or sole use of E. formosa could reduce the use of insecticides, slow down the development of insecticide resistance in whiteflies, and improve the efficiency of controlling the growth of whitefly populations in greenhouse vegetable production.

Dynamic error prediction and link strain feedback control for a novel heavy load multi-DOF envelope forming machine

Thin walled and high rib components (TWHRC) are widely used for rocket cabins, aircraft wings, panels and frames in aerospace equipment as critical load bearing structures. This paper is aimed to develop a novel multi-DOF envelope forming machine (MEFM) with parallel kinematic mechanism (PKM) to realize efficient manufacturing of TWHRC with high performance. Since the heavy load MEFM with PKM has many total differences with the light load PKM, such as dynamic error and precision control, this paper conducts research on dynamic error prediction modelling and precision control method for this novel heavy load MEFM.Firstly, the configuration of MEFM is developed and the kinematic model of MEFM is established. Then, a RFC (rigid-flexible coupling) and RFE (rigid finite element) coupling dynamic model of MEFM is established considering time-variation of kinematic configuration caused by large deformation of all the kinematic elements. Based on the dynamic model, the dynamic deformation and error of MEFM are predicted and their generation mechanisms are revealed. It is found that the linear compression deformation of two-force links is the largest among all the kinematic elements, and it is the most sensitive to the heavy forming load and the most insensitive to the installation error of strain gauges, thus suiting for the feedback of large deformation of MEFM. Based on the above findings, a novel link strain feedback and dynamic error compensation control method is proposed. Finally, experiments under different control methods are conducted, showing that the motion precision of envelope tool and forming precision of formed components under the proposed control method are remarkably improved compared with that under the traditional control method (The geometric deviation of formed components under the proposed control method is remarkably reduced to −18 ∼ 32um from −64 ∼ 54um under the traditional control method). The experimental results verify that the proposed dynamic error prediction model and link strain feedback control method for heavy load MEFM are reasonable.

Prestress Iterative Design and Precision Control Method for Cable-strut Structures using Enhanced Differential Evolution

Prestress Iterative Design and Precision Control Method for Cable-strut Structures using Enhanced Differential Evolution

Model based precise register control method for shaft-driven Roll-to-Roll(R2R) systems

Shaft-driven Roll-to-Roll (R2R) printing systems have advantages in keeping the printing rolls synchronously rotating, thereby reducing the register errors of R2R printing systems. However, tension oscillations and propagation are still inevitable due to other factors such as disturbances, which lead to the fluctuation of register errors. In this paper, a new mechanical model is established for the shaft-driven R2R systems. Then, a model-based precise control (MBPC) method is proposed, in which an implicit coupling algorithm is designed for the cooperate actions of the dancer rolls to rapidly suppress the tension oscillations and propagation. The stability of the proposed control system is proved via Lyapunov analysis. Moreover, the effectiveness of the proposed modeling and control method is verified via an industrial example. The results indicate that the proposed model can accurately characterize the dynamics of the R2R systems, and the MBPC can effectively eliminate the register errors caused by the tension oscillations and propagation, through the implicit coupling algorithm. Additionally, the results also demonstrate that the MBPC can increase the register precision of package manufacturing R2R systems into ±40 micrometers, which is superior to the existing control method.

Gradient‐Strained Van Der Waals Heterojunctions for High‐Efficient Photodetectors

AbstractMaximizing light‐to‐electricity conversion efficiency is a crucial challenge for the practical applications of 2D material photodetectors. However, due to the lack of stable and precise electronic structure control methods for 2D materials, the driving force of photogenerated carriers is insufficient that severely hinders the efficiency of separation and transport. Herein, a gradient‐modulated, stable and precise strain applied strategy for 2D materials is designed and constructed, which results in a significant improvement in the detect efficiency of ZnO/WSe2/graphene van der Waals heterojunction photodetectors. Different from the overall strain of all‐component materials in typical photodetectors, biaxial tensile strain is applied to WSe2 that can be precisely modulated by controlling the height of ZnO nanorods, while the strain is nearly unaffected to ZnO. As the strain modulation increases from 1.3% to 4.0%, the external quantum efficiency (EQE) of the heterojunction increases from 11.4% to 35.3%, representing a threefold increase. Furthermore, with increasing strain, the EQE can reach higher levels. Moreover, the strain‐enhanced conversion efficiency mechanism is elucidated that results from the synergistic effect of the strain‐induced WSe2 exciton convergence and the strain‐increased ZnO/WSe2 interface barrier, which enhances the carrier interface separation efficiency.

Imperatives for integrated weed management in vegetable production: Evaluating research and adoption

AbstractWeeds have a significant impact on vegetable production worldwide. These intensive cropping systems feature frequent tillage, fertilization and irrigation, providing ideal growing conditions for crops as well as certain weeds. Integrated weed management (IWM) can reduce reliance on herbicides by encouraging a systems approach to weed management. Using insights from global research and industry literature, we investigated the effectiveness of prevailing weed control methods, and evaluated emerging management practices and technologies for ongoing research and adoption. Weed control relies primarily on a relatively narrow range of herbicides as well as frequent tillage. Herbicides have negative impacts on soil, water and human health, while tillage impacts soil quality and function. Intensive cropping on smaller plots facilitates IWM, relying on multiple strategies including hand weeding, mulches, cover crops and cultural methods (e.g., crop rotations, timing). New herbicide options are suggested as an industry priority but are constrained by the lack of new chemistry and potential herbicide resistance. Refinement and adoption of non‐herbicide and emerging precision control methods into farm IWM in vegetables is more likely to be sustainable. This review is relevant to advanced vegetable production systems globally, but also to smallholder vegetable production in developing economies.

Hexagonal zoning deadbeat model predictive control of induction motor

AbstractDeadbeat model predictive control is known as a precise control method in motor control applications. Recently, finite set deadbeat control is applied to power electronics applications. A voltage‐based cost function is used to select the closest voltage vector to the reference vector by examining all possible states in the cost function. This method needs a high amount of computation when it is applied to multilevel inverters or virtual voltage vectors due to a considerable increase in the number of candidates. Some studies have been done to reduce the number of candidate voltage vectors and computation burden. The methodology in these methods is based on finding the adjacent area and applying the vertex vectors to the cost function. So, these strategies are multi‐step and complex. The hexagonal zoning deadbeat model predictive control is proposed and introduced. The basic idea of the proposed method is that each zone should contain only one vector. In this way, the area identification is equal to finding the optimum voltage selection. Hexagonal zoning is used, which simplifies the process of identifying the area. A simple area identification method is developed based on the reference voltage phase angle. The proposed method can be applied to different inverters with different spatial vector diagrams. Furthermore, the synthesis of the virtual vector is manipulated to reduce the torque and flux ripple. The proposed method is experimentally evaluated by applications to the virtual voltage switching of a two‐level inverter for the induction motor drive in this research.

Microfluidic programmable strategies for channels and flow.

This review summarizes programmable microfluidics, an advanced method for precise fluid control in microfluidic technology through microchannel design or liquid properties, referring to microvalves, micropumps, digital microfluidics, multiplexers, micromixers, slip-, and block-based configurations. Different microvalve types, including electrokinetic, hydraulic/pneumatic, pinch, phase-change and check valves, cater to diverse experimental needs. Programmable micropumps, such as passive and active micropumps, play a crucial role in achieving precise fluid control and automation. Due to their small size and high integration, microvalves and micropumps are widely used in medical devices and biological analysis. In addition, this review provides an in-depth exploration of the applications of digital microfluidics, multiplexed microfluidics, and mixer-based microfluidics in the manipulation of liquid movement, mixing, and splitting. These methodologies leverage the physical properties of liquids, such as capillary forces and dielectric forces, to achieve precise control over fluid dynamics. SlipChip technology, which branches into rotational SlipChip and translational SlipChip, controls fluid through sliding motion of the microchannel. On the other hand, innovative designs in microfluidic systems pursue better modularity, reconfigurability and ease of assembly. Different assembly strategies, from one-dimensional assembly blocks and two-dimensional Lego®-style blocks to three-dimensional reconfigurable modules, aim to enhance flexibility and accessibility. These technologies enhance user-friendliness and accessibility by offering integrated control systems, making them potentially usable outside of specialized technical labs. Microfluidic programmable strategies for channels and flow hold promising applications in biomedical research, chemical analysis and drug screening, providing theoretical and practical guidance for broader utilization in scientific research and practical applications.

Authentication of ten distinctive triterpenoids in Antrodia cinnamomea serves as a crucial aspect for ensuring the quality control of associated nutraceutical products.

Edible mushroom Antrodia cinnamomea is distinctive for its use in many health supplement products in relieving of diverse health-related conditions. A. cinnamomea is known for its rich array of bioactive secondary metabolites, predominantly terpenoids, that possess anti-inflammatory properties. Despite the abundance of these compounds, only some compounds have demonstrated notable anti-inflammatory activity. Moreover, there is a lack of established quality control methods specifically tailored to the active constituents of these products. Consequently, there is a great need for the development of precise and effective quality control methods for A. cinnamomea-based products, targeting their active components to ensure the consistency and reliability of these products in harnessing their anti-inflammatory potential. Herein we report a quantitative HPLC method for better evaluating the quality of A. cinnamomea based dietary supplements. Based on their bioactivities, we selected ten benchmark compounds, i. e. antcin K, (25S)-antcin H, (25R)-antcin H, (25R)-antcin C, (25S)-antcin C, (25R)-antcin A, 15α-acetyl-dehydrosulphurenic acid, versisponic acid D, dehydroeburicoic acid, and eburicoic acid and developed and validated a HPLC-UV method for quantification of these compounds simultaneously with high sensitivity, linearity and range, precision, and accuracy. Furthermore, we applied our method to quantify the commercially available A. cinnamomea containing supplements and found that the quality of these supplements varies greatly with only one product containing good amount of the active compounds. Our method provides a needed solution to quality control problem of the highly priced A. cinnamomea food and nutraceutical products that show great variety and inconsistency.

Driving range evaluation of electric vehicle with transcritical CO2 thermal management system under different battery temperature controls

Improper battery temperature will lead to reduced battery discharge efficiency and electric vehicle driving range. Endeavors to find an efficient and precise battery temperature control method for the transcritical CO2 thermal management system of electric vehicles, two evaporation temperature control methods for battery cooling were proposed. First, the effects of the control methods on battery temperature, optimal discharge pressure and coefficient of performance (COP) were simulated under typical operating conditions. Subsequently, a comparative simulation was conducted on the battery temperatures and COP of the two control methods under full cooling conditions. The results revealed that equal evaporation temperature control induced a reduction in battery temperature to 11 °C (suboptimal levels) under conditions of low ambient temperature and vehicle speed. Conversely, while unequal evaporation temperature control could maintain the battery temperature within the optimal range of 20–45 °C, it would result in a maximum COP drop of more than 20% under certain conditions. Furthermore, the effects of the two control methods on driving range under different ambient temperatures and vehicle speeds were studied. The reasults indicated that the ultimate influence of uneuqal evaporation temperature control on the quarterly average driving range was virtually negligible, peaking at 1.35%. Given the dual-objective constraints pertaining to the driving range and the battery cooling performance, it was concluded that uneuqal evaporation temperature control was the optimal choice for direct battery cooling.

Facile Fabrication Technique of Polymeric Ionic Liquids‐Coated Core–Shell Nanoparticles for Polymer Electrolyte Membranes

AbstractNanoparticles and nanofibers are widely used as components of polymer electrolytes for membranes in fuel cells, and many surface modification methods are reported. However, some fabrication techniques are complicated, and it is necessary to develop a simplified and precise control method. Herein, a facile fabrication method is reported for core–shell nanoparticles hierarchically coated with polymeric ionic liquids (PIL) and hydrophobic polymers as a material for polymer electrolytes. A hierarchical polymer layer on the surface of the SiO2 nanoparticles is easily constructed by repeating the facile polymer‐coating technique based on precipitation polymerization several times. The highest proton conductivity of the core–shell nanoparticles is 1.3 × 10−2 S cm−1 at 80 °C and 95% relative humidity. Although the hydrophobic polymers coated as a protective layer reduce the proton conductivity, the formation of the PIL enhances the proton conductivity in various temperature and humidity environments. Therefore, the proposed method enables the facile fabrication of polymer layers with multiple functions, such as a proton‐conductive PIL layer and hydrophobic polymer layers as protective layers on the surface of the nanoparticles. Furthermore, they are expected to be applied to energy supply and gas separation, including polyelectrolytes, for the realization of a sustainable society.