Control Key Technologies Research Articles

Infection Process of Alfalfa Root Rot Caused by Fusarium acuminatum

Fusarium spp. can cause root rot in alfalfa, leading to the death of the whole plant, which seriously affects the yield and quality of alfalfa. This study used a Fusarium acuminatum strain labeled with green fluorescent protein (GFP) to observe the infection process of F. acuminatum on alfalfa by confocal fluorescence microscopy. The aim of this study was to reveal the infection mechanism of alfalfa Fusarium root rot at the cellular histological level. The results showed that conidia of F. acuminatum attached to the surface of the root and germinated at one day post-inoculation, the mycelium then entered the vascular bundle tissue of the alfalfa root at 5 days post-inoculation, reached the base of the plant stem at 14 days post-inoculation, and colonized the stem of the first and second compound leaf at 28 and 49 days post-inoculation, respectively. Moreover, the experiment, which sprayed a spore suspension, showed that the conidia of F. acuminatum could spread through the air to infect the pericarp and seed coat tissue of the pod. For the first time, we report the infection process of alfalfa Fusarium root rot caused by F. acuminatum and clarify that F. acuminatum can initially infect the root tissue of alfalfa, colonize the bottom stem of the plant through systematic infection, and eventually cause the plant to wilt and die. The results reveal the infection mechanism of F. acuminatum at the cell level via histology and provide theoretical support for the development of control strategies and key control technologies for alfalfa root rot.

Formation Mechanism and Prevention Technology of Mine Water Disaster under Complex Conditions

With the continuous westward shift of China’s coal production center, the western mining areas will play an increasingly important role in ensuring national energy security. It is urgent to extract coal economically and efficiently and realize scientific mining under the premise of ensuring the safe and environmental capacity. This paper systematically summarizes the research progress of coal seam separation water disaster at home and abroad, and elaborates the problem of coal seam separation water disaster from four aspects: formation mechanism of coal seam separation water, disaster-causing mechanism, prediction and early warning of water disaster and key prevention and control technologies. This paper summarizes the research on mining overlying strata separation and the formation mechanism of overlying strata separation water, and summarizes the formation of coal seam overlying strata separation water into three basic conditions: water separation, the existence of recharge water around the separation bed, and the separation space lasting long enough. However, the prevention and control of coal mine water disaster under complex geological conditions is an important problem restricting coal mine safety at present. The water damage prediction of overlying strata separation is summarized from three aspects: prediction of the location of available water separation, prediction of the periodicity of water inrush and prediction of the amount of water inrush, according to the development characteristics of bed separation. In this paper, the water damage prediction of overlying strata separation is summarized from three aspects: prediction of the location of available water separation, prediction of the periodicity of water inrush and prediction of the amount of water inrush. According to the development characteristics of bed-separation and the location of bed-separation water, the main prevention and control methods of bed-separation water damage, such as diversion hole, advance drain hole and ground direct pump hole, are proposed.

A Safe and Efficient Double-Gene-Deleted Live Attenuated Immersion Vaccine to Prevent the Disease Caused by the Infectious Spleen and Kidney Necrosis Virus.

Infectious diseases seriously threaten sustainable aquaculture development, resulting in more than $10 billion in economic losses annually. Immersion vaccines are emerging as the key technology for aquatic disease prevention and control. Here, a safe and efficacious candidate immersion vaccine strain (Δorf103r/tk) of infectious spleen and kidney necrosis virus (ISKNV), in which the orf103r and tk genes were knocked out by homologous recombination, is described. Δorf103r/tk was severely attenuated in mandarin fish (Siniperca chuatsi), inducing mild histological lesions, a mortality rate of only 3%, and eliminated within 21 days. A single Δorf103r/tk immersion-administered dose provided long-lasting protection rates over 95% against lethal ISKNV challenge. Δorf103r/tk also robustly stimulated the innate and adaptive immune responses. For example, interferon expression was significantly upregulated, and the production of specific neutralizing antibodies against ISKNV was markedly induced postimmunization. This work provides proof-of-principle evidence for orf103r- and tk-deficient ISKNV for immersion vaccine development to prevent ISKNV disease in aquaculture production. IMPORTANCE Global aquaculture production reached a record of 122.6 million tons in 2020, with a total value of 281.5 billion U.S. dollars (USD). However, approximately 10% of farmed aquatic animal production is lost due to various infectious diseases, resulting in more than 10 billion USD of economic waste every year. Therefore, the development of vaccines to prevent and control aquatic infectious diseases is of great significance. Infectious spleen and kidney necrosis virus (ISKNV) infection occurs in more than 50 species of freshwater and marine fish and has caused great economic losses to the mandarin fish farming industry in China during the past few decades. Thus, it is listed as a certifiable disease by the World Organization for Animal Health (OIE). Herein, a safe and efficient double-gene-deleted live attenuated immersion vaccine against ISKNV was developed, providing an example for the development of aquatic gene-deleted live attenuated immersion vaccine.

A Landslide Warning Method Based on K-Means-ResNet Fast Classification Model

Landslide early warning is a key technology for effective landslide prevention and control. However, the traditional landslide early warning mainly makes decisions through thresholds, and if the thresholds are not selected properly, it will lead to missing alarms and false alarms frequently. To resolve this problem, this study proposes a landslide early warning algorithm based on a K-means-ResNet model. This method uses the K-means method to cluster the landslide deformation state, and then uses ResNet to classify the landslide rainfall and deformation data, so as to realize the threshold-free judgment and early warning of landslide deformation state. The model was applied to the Zhongma landslide, Guangxi Province, China, and the Shangmao landslide, Hunan Province, China, for validation and evaluation. The results showed that the accuracy, precision and recall of the proposed model can reach 0.975, 0.938, 0.863 and 0.993, 0.993, 0.925, respectively, for classifying the deformation states of the two landslides, and the classification results are better than those of the baseline model. Compared with the threshold-based early warning method, the proposed early warning method does not require artificial determination of threshold parameters and can effectively identify landslide deformation states, which can not only reduce false alarms and missing alarms but also improve the reliability of early warning.

Development and prospects of key technology for submarine atmospheric environment control

Development and prospects of key technology for submarine atmospheric environment control

Flight Control Technology Advancements and Challenges for Future Rotorcraft 40th Alexander A. Nikolsky Honorary Lecture

The goal of my 40th Alexander A. Nikolsky Honorary Lecture and journal paper is to highlight the key flight control technology advances of the past 50 years and demonstrate how these advances are being applied and extended to the new family of rotorcraft: modern high-speed military rotorcraft, eVTOL urban air mobility, and advanced air mobility aircraft. The first part of this journal paper reviews flight control technologies drivers that are unique to rotorcraft and highlights key advances of the past 50 years in the areas of handling-qualities requirements (ADS-33), physics-based models, system identification, and flight control. A central theme is the shift from time-domain to frequency-domain based characterization of the closed-loop response and design methods for rotorcraft that have become increasingly dependent on sophisticated feedback control systems to achieve closed-loop stability, disturbance rejection, and most importantly closed-loop handlingqualities response for all-weather operations. Frequency-domain analysis, design, and test methods of the past 50 years are highlighted relating key advances in each discipline and two integrated example success stories. In the second part of this paper, we consider the key challenges, advancements, and needed future research for four new classes of rotorcraft: the military future vertical lift family of high-speed rotorcraft, unmanned autonomous systems/urban air mobility based on fielded conventional helicopters, small electric VTOL unmanned aerial vehicle rotorcraft, and larger eVTOL urban air mobility rotorcraft. The next sections look across the challenges and solution spaces that are common to these four new classes of rotorcraft as a blueprint for needed research advances. Finally, this paper takes a step back and considers the lessons-learned and key takeaways from the author's perspective as a career-long flight control engineer/researcher, Flight Control Technology Group leader, and senior technologist.

Energy Harvesting and Thermal Management System in Aerospace

Energy harvesting and thermal management in spacecraft refer to the adjustment, distribution, and comprehensive use of uniform adjustment, allocation, and integrated use of the spacecraft and subsystems, which have the advantages of reducing energy consumption and improving the overall performance of the spacecraft. The study is first briefly elaborated on the research progress of energy harvesting and thermal management, and then introduces the key thermal control technology of thermal management, mainly thermal bus systems, heat pump technology, and passive thermal control technology. Finally, the future development direction and research focus of thermal management are proposed, which lays a foundation for the future development of energy harvesting and thermal management technology.

Prisons of Rubble and Paper in Colonial Saint-Domingue and Beyond

Ample scholarship from Foucault onward has probed the origins of prisons as a key technology for modern state control, but overemphasizes the revolutionary era as a moment of invention. The prison existed much earlier and, as this research demonstrates, gradually became a favored tool among many widely-utilized alternatives. Other historians have explored early modern strategies such as exile, used most often to punish recalcitrant subjects when other strategies did not work. This evidence points to a general pattern whereby these forms of control coexisted and even overlapped in an array of punitive options. I theorize coercive strategies as existing together within a “punitive matrix,” in which imprisonment operated as one among many methods of state control, alongside others such as galley labor, banishment, and corporal punishment. Beginning with evidence from Saint-Domingue in the first half of the eighteenth century about prisons, building out from Jean Clavier’s Léogane in the 1740s. It then turns to the archival sources themselves to understand how colonial administrators described prisons. Read together, this evidence highlights the limited power of prisons, and imprisonment, to control imperial subjects, while elucidating some of the pathways chosen by those subjects.

High robustness energy management strategy of hybrid electric vehicle based on improved soft actor-critic deep reinforcement learning

As a hybrid electric vehicle (HEV) key control technology, intelligent energy management strategies (EMSs) directly affect fuel consumption. Investigating the robustness of EMSs to maximize the advantages of energy savings and emission reduction in different driving environments is necessary. This article proposes a soft actor-critic (SAC) deep reinforcement learning (DRL) EMS for hybrid electric tracked vehicles (HETVs). Munchausen reinforcement learning (MRL) is adopted in the SAC algorithm, and the Munchausen SAC (MSAC) algorithm is constructed to achieve lower fuel consumption than the traditional SAC method. The prioritized experience replay (PER) is proposed to achieve more reasonable experience sampling and improve the optimization effect. To enhance the “cold start” performance, a dynamic programming (DP)-assisted training method is proposed that substantially improves the training efficiency. The proposed method optimization result is compared with the traditional SAC and deep deterministic policy gradient (DDPG) with PER through the simulation. The result shows that the proposed strategy improves both fuel consumption and possesses excellent robustness under different driving cycles.

Review of Investigations on Hazard Chains Triggered by River-Blocking Debris Flows and Dam-Break Floods

The Tibetan Plateau suffers from various types of geohazards (collapses, landslides, and debris flows.) due to abrupt changes in complex topography and weather conditions. Global warming and frequent high-intensity earthquakes in recent years have exacerbated the situation. Collapses and landslides provide vast amount of soil and debris which are conveyed downstream by runoff caused by extreme rainfalls to form large-scale debris flows; then, the debris flows block rivers and finally form dam-break floods, that is, a hazard chain triggered by debris flows. Along the evolution direction of the hazard chain, the affected areas are constantly amplified. This study first summarizes the related research studies on river blockage, debris-flow dam failure, and the hazard chain triggered by debris flows and then points out the drawbacks of existing research studies. Overall, the research (including mechanism, risk assessment, key prevention, and control technologies) on the hazard chain triggered by debris flows is still in its infancy and is disconnected among single hazard types in the hazard chain; meanwhile, the understanding of the mechanism of debris flow blocking the river is not enough; the established model and discriminant have minimal application scope, and there is no empirical model and dynamic model of debris-flow dam failure. Finally, several key scientific issues of this field were raised: 1) it is necessary to elaborate the coupling mechanism of debris-flow dam formation and construct the discriminant and numerical model of debris flow blocking the river with high precision and a wide application range. 2) It is necessary to further study the failure mechanism of a debris-flow dam, construct the numerical model of the failure process of a debris-flow dam, and accurately simulate the outburst flood hydrograph. 3) It is necessary to clarify the critical transformation conditions and dynamic evolution process of the hazard chain caused by debris flows, complete the accurate quantitative simulation of the whole disaster chain process, then establish a complete risk assessment system of the hazard chain, and finally develop some key prevention and control technologies suitable for the hazard chain.

Instability Mechanism and Key Control Technology of Deep Soft Rock Roadway under Long‐Term Water Immersion

More and more attention has been paid to the supporting problem of deep soft rock roadway floor with long‐term water immersion in recent years. However, the existing soft rock roadway support technology rarely takes into account the influence of the immersion softening phenomenon of the roadway floor and the self‐supporting structure characteristics of the surrounding rock on the stability of the surrounding rock at the same time, and the influence of the creep characteristics of rock on the deformation zone of the surrounding rock requires further research on the nature and division of the self‐supporting structure of the surrounding rock. In response to the issues mentioned, based on the loading and unloading properties of the surrounding rock of the soft rock roadway, a new concept of the internal and external self‐bearing structure was proposed. The fact of water‐immersed mudstone softening in the soft rock roadway floor was revealed through the field practice, and the shape of the internal and external bearing structure was determined based on the in situ monitoring results. Then, the instability mechanism of the internal and external self‐bearing structure of the surrounding rock was analyzed, the position of the critical control point was calculated, and the key control technology based on the method of controlling floor heave by using double‐row anchor cables to control the deformation of the roadway sides was put forward. Finally, the field industrial test showed that this support technology can effectively control the deformation and failure of soft rock roadway in the case of water immersion on the floor. This work can provide a technical reference for similar roadway support designs.

Model Predictive Control of Soft Constraints for Autonomous Vehicle Major Lane-Changing Behavior With Time Variable Model

Changing lane must not only ensure the safety of the vehicle itself, but also ensure the patency of the traffic flow of the original lane and the target lane. Therefore, successful lane-changing is a key technology for autonomous vehicle control. In order to avoid collisions and ensure the smooth flow of traffic, in this paper a vehicle dynamics state model with time variable is established as plant, and the lateral force of the steering wheel is further optimized through Model Predictive Control(MPC), and then the steering wheel angle is obtained to complete the lane-changing operation. The longitudinal and lateral logic controllers designed through soft constraints can better achieve the results of successful lane-changing and unsuccessful return to the original lane, and the lane-changing characteristics within the safety corridor are analyzed in several ways. The simulation analysis of lane-changing strategy at different vehicle velocities provides helpful guidance for the design of autonomous vehicle controllers.

Research on Plastic Zone Evolution Law of Surrounding Rock of Gob-Side Entry Retaining under Typical Roof Conditions in Deep Mine

To solve the control problem of the surrounding rock of gob-side entry retaining under typical roof conditions in deep mines, we conduct theoretical analysis, numerical simulation, and actual measurements. Starting from the plastic zone of the surrounding rock, the serious damage area, the degree and scope of damage, and the dynamic evolution process of the surrounding rock of the gob-side entry retaining are systematically analyzed under four typical roof conditions in deep mines; the expansion and evolution laws of the plastic zone of the surrounding rock are expounded; and a key control technology is proposed. The results indicate that (1) the plastic failure of surrounding rock was concentrated mainly on the coal side and on the floor, especially in the filling body. The plastic zone of the surrounding rock of the gob-side entry retaining with the thick immediate roof was widely distributed and deep, but the plastic failure of the filling body was not obvious. The plastic failure of the surrounding rock of the gob-side entry retaining with the compound roof was mainly concentrated on the roof, filling body, and floor of the filling area. (2) According to the typical roof conditions of the deep gob-side entry retaining, the order of the degree of damage to the surrounding rock was as follows: thick immediate roof, compound roof, thin immediate roof, and thick-hard roof. (3) A “multisupport structure” control system is proposed for the gob-side entry retaining in a deep mine, including measures for enhancing the bearing performance of the anchorage system, increasing the strength of the cataclastic coal-rock mass, enhancing the bearing capacity of the filling body, and increasing the bearing capacity on the tunnel side. The proposed technology was applied to the deep gob-side entry retaining project in the east area of Panyi Mine, and it effectively fulfilled the reuse requirements of gob-side entry retaining in deep mines.

Giant Enhancement of Air Lasing by Complete Population Inversion in N_{2}^{+}.

A fine manipulation of population transfer among molecular quantum levels is a key technology for control of molecular processes. When a light field intensity is increased to the TW-PW cm^{-2} level, it becomes possible to transfer a population to specific excited levels through nonlinear light-molecule interaction, but it has been a challenge to control the extent of the population transfer. We deplete the population in the X^{2}Σ_{g}^{+}(v=0) state of N_{2}^{+} almost completely by focusing a dual-color (800nm and 1.6 μm) intense femtosecond laser pulse in a nitrogen gas, and make the intensity of N_{2}^{+} lasing at 391nm enhanced by 5-6 orders of magnitude. By solving a time-dependent Schrödinger equation describing the population transfer among the three lowest electronic states of N_{2}^{+}, we reveal that the X^{2}Σ_{g}^{+}(v=0) population is depleted by the vibrational Raman excitation followed by the electronic excitation A^{2}Π_{u}(v=2,3,4)←X^{2}Σ_{g}^{+}(v=1)←X^{2}Σ_{g}^{+}(v=0), resulting in the excessive population inversion between the B^{2}Σ_{u}^{+}(v=0) and X^{2}Σ_{g}^{+}(v=0) states. Our results offer a promising route to efficient population transfer among vibrational and electronic levels of molecules by a precisely designed intense laser field.

Surrounding Rock Failure Characteristics and Key Control Technology of Double- sided Mining Roadway

Surrounding Rock Failure Characteristics and Key Control Technology of Double- sided Mining Roadway

Application of Load Optimization Control of Thermal Power Unit Based on the Characteristics of Regulating Valve

In the long-term operation of thermal power units, the nonlinear and more complex viscous faults often occur in the regulator valve, which have obvious adverse effects on the dynamic performance of the load control. By using two point line models and Presiach models that are switched to each other to describe the switch asymmetry of the regulating valve and the different viscosity characteristics, the viscous fault of the regulating valve is effectively diagnosed, and the statistical consistency of the estimated values of model parameters are proved. Several key control technologies of thermal unit are given, and the control method of compensating the viscous fault of the regulating valve is presented, which weakens the adverse effect of the non-linear characteristics of the control valve on the dynamic control performance, and makes the main variables such as main steam pressure of unit achieve good dynamic performance.

Research on Path Planning of Aircraft Based on Improved Genetic Algorithm

As for the optimal design of aircraft, route planning is an important part of mission planning system and a key technology for autonomous control of aircraft. In order to find the optimal route quickly, an aviation network model based on navigation point flight is designed. The cost function is generated by considering the distance between nodes, weather and the density of the aircraft, and the optimal route in the model is planned by using the improved genetic algorithm. The simulation results show that this method can realize the optimal design of the flight path of the aircraft in the aviation network.

Monthly Electricity Consumption Forecasting Method Based on X12 and STL Decomposition Model in an Integrated Energy System

With the rapid development and wide application of distributed generation technology and new energy trading methods, the integrated energy system has developed rapidly in Europe in recent years and has become the focus of new strategic competition and cooperation among countries. As a key technology and decision‐making approach for operation, optimization, and control of integrated energy systems, power consumption prediction faces new challenges. The user‐side power demand and load characteristics change due to the influence of distributed energy. At the same time, in the open retail market of electricity sales, the forecast of electricity consumption faces the power demand of small‐scale users, which is more easily disturbed by random factors than by a traditional load forecast. Therefore, this study proposes a model based on X12 and Seasonal and Trend decomposition using Loess (STL) decomposition of monthly electricity consumption forecasting methods. The first use of the STL model according to the properties of electricity each month is its power consumption time series decomposition individuation. It influences the factorization of monthly electricity consumption into season, trend, and random components. Then, the change in the characteristics of the three components over time is considered. Finally, the appropriate model is selected to predict the components in the reconfiguration of the monthly electricity consumption forecast. A forecasting program is developed based on R language and MATLAB, and a case study is conducted on the power consumption data of a university campus containing distributed energy. Results show that the proposed method is reasonable and effective.

Review on applications of remote sensing in urban flood modeling

Urban flooding is serious in China. More than 360 cities have suffered rainstorm floods from 2007 to 2013. Floods in Beijing, Guangzhou, Jinan, et al. have caused serious casualties. In recent years, sea-views in cities have repeated here and there, and rainstorm induced flood has gradually become a chronic illness in many large and medium-sized cities in China. Simulation model for floods is a key technology for urban flood control and land use planning, and play a crucial role in the construction of urban water conservancy projects and infrastructures such as urban drainage system and sponge city. With the continuous and rapid development of the economics and society, urban flood risk warning and management requires a higher demand on the efficiency and elaboration of flood simulation. Obviously, the degree of elaboration on flood simulation highly depends on the temporal and spatial resolution of the basic input data. Rainfall data with smaller time intervals will present more comprehensive rainfall characteristics and further reflect the characteristics of flood processes. Meanwhile, higher resolution terrain data can reflect subtle ground features of urban surface such as buildings, curbs, bridges, etc. By summarizing and analyzing the literature on the researches of hydrological modeling with the utilization of remote sensing data, the application of remote sensing data (including meteorological and hydrological data, and surface information based on remote sensing) in flood simulation is reviewed. Frequently used remote sensing data sources with relatively high precision such as LiDAR (light imaging, detection, and ranging), InSAR (interferometric synthetic aperture radar), oblique photography and hyperspectral remote sensing as well as their applications are presented. Advanced technologies and methods (airborne LiDAR and UAV Oblique Photography) producing basic remote sensing information used in urban flood modeling are presented. Finally, an example is given to illustrate the extraction framework of the basic information of urban flood simulation based on remote sensing, and the prospect to apply remote sensing technology in urban flood simulation is also presented. It is pointed out that flood simulation will be more effective and refined with the support of massive multi-source data in the future. At the same time, rich data sources also bring the following challenges and opportunities: (1) Rapidly increasing amount of high-resolution remote sensing data poses greater challenges to data storage and management, while high-performance distributed storage technologies and data processing technologies can provide solutions for this objective. (2) Massive data and the relatively low processing and utilization capacity will cause a huge waste of resources. Based on data analysis methods such as machine learning and data assimilation, massive multi-source data will be integrated to form a comprehensive database for urban flood modeling, which can provide scientific and technological support for modern urban construction and management. (3) Urban flood simulation with high resolution is extremely computational intensive that the time consumption will exponentially increase. However, this is unacceptable for rapid and efficient urban flood forecasting and early warning. High-performance computing technology such as GPU-based parallelization on CUDA platform will greatly benefit for urban flood simulation.

排污入海河口及临近海域水质中的生化需氧量检测关键控制技术

排污入海河口及临近海域水质中的生化需氧量检测关键控制技术