Joint Control System Research Articles

Parameter Tuning and Positioning Strategy of VD and TMD Joint Control System for Multi-Modal Vibration of Stay Cables

Stay cables are becoming slender and their fundamental frequencies are becoming lower with the span of bridges increasing, thus leading to the occurrence of multi-modal vibration under various excitations. As a simple and effective strategy for cable vibration mitigation, the external damper is widely used in practice. However, one damper normally can target only fewer modes and poses limited effects on the control of multi-modal vibration. This paper proposed the use of a joint control system combining a viscous damper and a tuned mass damper for mitigating the multi-modal vibration of stay cables, followed by the optimization methodology of tuning and positioning. The control performance of the joint system was evaluated by numerical simulations. The feasibility of the joint control system was validated by analyzing the results of the comparative study, therefore providing a possible solution to multi-modal and high-modal vibration of stay cables.

Evaluation of the Demand Flexibility Potential Through Joint Optimization of Building Thermal Response and Indoor Air Quality in Commercial Buildings

Abstract Large commercial buildings may display demand flexibility, which reduces electric energy expenses for the building owner and carbon emissions from grid operations, provides distributed energy resources, and increases the penetration of renewable energy sources. Demand-controlled ventilation (DCV) and building thermal mass control can individually and jointly provide such flexibility. The performance and financial payback of these technology options can be dramatically improved if based on hourly electric prices and carbon emissions rates. In this study, a modeled but actual large office building, simulated using New York City hourly electric prices, hourly CO2e emissions rates, and weather data for the summer 2019 cooling season is based on these dynamic driving parameters. A joint optimization of a building’s thermal mass and indoor CO2 content is presented. Superior energy savings and carbon emissions reductions are found for the joint optimization scenario when compared to both the baseline operation and individual optimization of building thermal mass and indoor CO2 content. These findings motivate the development of a real-time joint control system that utilizes closed-loop model predictive control (MPC) to optimally harness both sources of demand flexibility, a system that would require the future development of forecasting algorithms for external and control-oriented system models.

A Joint Communication and Control System for URLLC in Industrial IoT

Ultra reliable low latency communication (URLLC) is playing an important role in future wireless networks, such as industrial Internet of things (IIoT). Enormous industrial devices are requiring instant and highly-frequent control services, namely delay sensitive control, in order to improve the human safety or the operation accuracy. In this paper, a joint communication and delay sensitive control (JCDSC) system with URLLC is studied, where the control intervals are much shorter than the transmission latency. The control performance, known as the mean square error (MSE) of the plant states, are analysed in theory. The optimal blocklength of the control codewords, the data rate, as well as the minimum required control periods are then obtained, in order to minimize the control latency. Simulation results validate our theoretical analysis, while also demonstrating that an optimal blocklength of codewords should be selected in order to reduce the control latency.

Rudder/fin joint anti-rolling control system based on interference model predictive control and sliding mode observer

To overcome the difficulties of time-varying disturbance, model mismatch, and frequent operation in the rudder/fin joint control system, an interference model predictive control (I-MPC) rudder/fin joint control system with sliding mode observer is proposed. Considering that the model mismatch problem occurs when the ship is sailing, the model mismatch and external disturbance are regarded as the total disturbance. A discrete 3-degree-of-freedom ship disturbance mathematical model is established. The rudder angle and fin angle are selected as the system inputs, then a sliding mode observer is designed to observe the time-varying disturbance and system output in real time. Different from traditional MPC and feedforward compensation, I-MPC will predict the output based on the disturbance observation value, and the control law is solved under rudder/fin angle and angular velocity constraints. Simulation results show that the proposed method improves the tracking performance and anti-disturbance performance of the rudder/fin system. The observer has high observation accuracy for constant, sinusoidal, and time-varying disturbances. Mechanism wear and energy loss caused by frequent operation are avoided.

Implementation of the Robson Classification in Greece: A Retrospective Cross-Sectional Study.

Cesarean sections have become the most commonly performed operations around the world. The World Health Organization recommended the use of the Robson classification system as a universal standard to establish a joint control system in healthcare facilities. The aim of this study was to implement the Robson classification for the first time in Greece to identify trends in cesarean births and examine the groups of women who are the main contributors to the increasing rates. Moreover, the indicators for cesarean sections will be evaluated as per the Robson classification. In the sample analysis, we included the records of 8572 women giving birth in one private health facility in Greece. A total of 8572 women gave birth during the study period, of which 5224 (60.9%) were cesarean section births and 3348 (39.1%) were vaginal births. In our study, according to the Robson classification, the largest contributors to the overall CS rate were as follows: (a) nulliparous women with a single cephalic term pregnancy, who were either labor induced or delivered by cesarean section before labor-Group 2 (34.6%); (b) multiparous women with a single cephalic term pregnancy and at least one previous cesarean section-Group 5 (30.7%); (c) women with a single cephalic preterm pregnancy-Group 10 (11.7%); (d) women with multiple pregnancies-Group 8 (7.0%). Our study is expected to assist policymakers in Greece in planning further interventions for each subgroup of women in order to reduce the overall CS rate and unnecessary CSs.

Construction and Application of “Active Prediction-Passive Warning” Joint Impact Ground Pressure Resilience Prevention System: Take the Kuan Gou Coal Mine as an Example

Abstract With the increasing depth and intensity of coal mining, the impact on ground pressure has become one of the main disasters facing mining, seriously threatening mine safety. Introducing the concept of toughness urban design, building a joint toughness prevention and control system based on active prediction and analysis of the impact pressure risk at the back mining face according to the geological deposit conditions and mining technology conditions and passive warning using monitoring data to explore the impact precursor characteristics is an important basis for impact pressure management and has important engineering significance to ensure the safe back mining. In this paper, firstly, the whole working face is divided into small unit areas, and the BP neural network prediction model is constructed to predict and analyze each small unit separately, and the distribution of impact ground pressure hazard level in different areas of the working face is derived. Next, a FLAC numerical model was established to analyze the stress distribution and migration characteristics at different retrieval distances of the working face and to explore the main distribution areas of impact hazard. Finally, the trend method, critical value method, and dynamic rate of change method were applied to determine the early warning indicators of impact ground pressure in the Kuan Gou coal mine, establish a comprehensive early warning method of impact ground pressure applicable to the Kuan Gou coal mine, and carry out field application with good effect. The findings of this paper have good scientific significance and reference value for promoting impact hazard analysis and early warning in mines with similar geological conditions and mining technology conditions in China.

Research on the Impact of Atmospheric Self-Purification Capacity on Environmental Pollution: Based on the Threshold Effect of Environmental Regulation

In China, Hebei Province and Guangdong Province have many pollution-intensive industries; yet Hebei suffers more serious atmospheric or environmental pollution than Guangdong. To explain the phenomenon, this paper chooses the statistical data of 286 prefecture-level cities in the Chinese mainland from 2005 to 2018 and empirically tests the spatial effect and threshold characteristics of atmospheric self-purification capacity on environmental pollution by using the spatial autoregression model (SAR), spatial Durbin model (SDM), and panel threshold model. As evinced, the local atmospheric self-purification capacity has a significant inhibitory effect on environmental pollution, and the absolute value of the direct effect coefficient reaches 1.337. Simultaneously, atmospheric self-purification capacity has a threshold effect on environmental pollution. The threshold value of environmental regulation as a threshold variable is 11.6349. This means that when the level of environmental regulation proves higher than 11.6349, it attenuates the inhibitory effect of the atmospheric self-purification capacity on environmental pollution. As the heterogeneity research unveils, atmospheric self-purification capacities in various regions form a significant correlation with environmental pollution. This paper suggests that local governments should strengthen environmental regulation and construct an inter-regional joint prevention and control system for atmospheric-pollution governance to enhance the atmospheric self-purification capacity.

Retracted] Study on the Mechanism of Pathological Recognition Based on Bioelectrical Impedance Spectrum to the Elbow Joint

The elbow joint is prone to stiffness and adhesion after trauma or surgery. High‐energy trauma easily led to loss of mobility of the elbow joint. Mild trauma can also cause stiffness in the elbow joint. In order to investigate the pathogenesis of stiffness and adhesion in elbow joint, a feedback‐type elbow joint control system based on network is proposed in this paper. The simulation results show that it has significant differences in elbow bioelectrical impedance in patients with elbow trauma, and this new method realizes the control strategy of converting the patient’s elbow joint pathological information into elbow joint orthosis control information.

Non-linear multimodal integration in a distributed premotor network controls proprioceptive reflex gain in the insect leg

Producing context-appropriate motor acts requires integrating multiple sensory modalities. Presynaptic inhibition of proprioceptive afferent neurons1-4 and afferents of different modalities targeting the same motor neurons (MNs)5-7 underlies some of this integration. However, in most systems, an interneuronal network is interposed between sensory afferents and MNs. How these networks contribute to this integration, particularly at single-neuron resolution, is little understood. Context-specific integration of load and movement sensory inputs occurs in the stick insect locomotory system,6,8-12 and both inputs feed into a network of premotor nonspiking interneurons (NSIs).8 We analyzed how load altered movement signal processing in the stick insect femur-tibia (FTi) joint control system by tracing the interaction of FTi movement13-15 (femoral chordotonal organ [fCO]) and load13,15,16 (tibial campaniform sensilla [CS]) signals through the NSI network to the slow extensor tibiae (SETi) MN, the extensor MN primarily active in non-walking animals.17-19 On the afferent level, load reduced movement signal gain by presynaptic inhibition. In the NSI network, graded responses to movement and load inputs summed nonlinearly, increasing the gain of NSIs opposing movement-induced reflexes and thus decreasing the SETi and extensor tibiae muscle movement reflex responses. Gain modulation was movement-parameter specific and required presynaptic inhibition. These data suggest that gain changes in distributed premotor networks, specifically the relative weighting of antagonistic pathways, could be a general mechanism by which multiple sensory modalities are integrated to generate context-appropriate motor activity.

Can the joint regional air pollution control policy achieve a win-win outcome for the environment and economy? Evidence from China

We explore the effect of the Joint Prevention and Control System of Regional Air Pollution (JPCSRAP) in China from a composite environmental-economic perspective, based on Chinese urban data, using the PSM-DID method. We find that JPCSRAP can achieve a win-win outcome for the environment and economy, namely by reducing air pollution while achieving economic growth, with these effects increasing over time. However, the implementation effects differ by region. The effects of JPCSRAP are due to the strengthening of collaborative governance between cities, the upgrading of the industrial structure, and the encouragement of technological innovation. Our research provides an important reference for developing countries to achieve effective air pollution control and economic growth. • We study China’s Joint Prevention and Control System of Regional Air Pollution. • The JPCSRAP can achieve a win-win outcome for both the environment and the economy. • There is spatial and temporal heterogeneity in the policy effects of JPCSRA. • JPCSRAP strengthens the collaborative governance between cities. • JPCSRAP upgrades industrial structure and encourages technological innovation.

Influential Nodes Identification in the Air Pollution Spatial Correlation Weighted Networks and Collaborative Governance: Taking China's Three Urban Agglomerations as Examples.

Nowadays, driven by green and low-carbon development, accelerating the innovation of joint prevention and control system of air pollution and collaborating to reduce greenhouse gases has become the focus of China’s air pollution prevention and control during the “Fourteenth Five-Year Plan” period (2021–2025). In this paper, the air quality index (AQI) data of 48 cities in three major urban agglomerations of Beijing-Tianjin-Hebei, Pearl River Delta and Yangtze River Delta, were selected as samples. Firstly, the air pollution spatial correlation weighted networks of three urban agglomerations are constructed and the overall characteristics of the networks are analyzed. Secondly, an influential nodes identification method, local-and-global-influence for weighted network (W_LGI), is proposed to identify the influential cities in relatively central positions in the networks. Then, the study area is further focused to include influential cities. This paper builds the air pollution spatial correlation weighted network within an influential city to excavate influential nodes in the city network. It is found that these influential nodes are most closely associated with the other nodes in terms of spatial pollution, and have a certain ability to transmit pollutants to the surrounding nodes. Finally, this paper puts forward policy suggestions for the prevention and control of air pollution from the perspective of the spatial linkage of air pollution. These will improve the efficiency and effectiveness of air pollution prevention and control, jointly achieve green development and help achieve the “carbon peak and carbon neutrality” goals.

Development of a magnetorheological elastomer rubber joint with fail-safe characteristics for high-speed trains

The stiffness of the train’s rubber joint at the primary suspension system has a crucial influence on the operation stability and curve-passing performance. As traditional rubber joint only provides unadjustable parameters, they cannot meet the conflicting stiffness requirements when the train is running at high speed on straight track and passing through the curve track. To solve this problem, this paper proposed a new rubber joint with fail-safe characteristics based on magnetorheological elastomer (MRE). The joint stiffness is controlled by a hybrid magnetic field generated by permanent magnets and electromagnets. With this hybrid magnetic field, the initial stiffness of the MRE joint can be designed to be hard so as to suppress the hunting motions and vibrations of wheelsets and thus keep the trains’ high-speed stability; furthermore, the stiffness can decrease by energizing the electromagnets when passing through a curve track. With this characteristic, the joint can guarantee the safety of the train at high operation speed even when the joint control system fails. The prototype of the MRE joint was fabricated and assembled. Stiffness controllability of the MRE joint was tested using a Material Testing Systems machine. The result reveals that the stiffness of this MRE joint can be controlled effectively. According to the testing results, a new phenomenological model was built to predict the joint’s dynamic performance. Then this established model was integrated into dynamic models of trains to numerically evaluate the new joint’s influence on the train’s stability and trafficability. The evaluation result shows that the proposed MRE joint is fully effective on providing controllable stiffness to satisfy the conflicting stiffness requirement with fail-safe characteristics.

Development of a magnetorheological elastomer rubber joint with fail-safe characteristics for high-speed trains

Abstract The stiffness of the train’s rubber joint at the primary suspension system has a crucial influence on the operation stability and curve-passing performance. As traditional rubber joint only provides unadjustable parameters, they cannot meet the conflicting stiffness requirements when the train is running at high speed on straight track and passing through the curve track. To solve this problem, this paper proposed a new rubber joint with fail-safe characteristics based on magnetorheological elastomer (MRE). The joint stiffness is controlled by a hybrid magnetic field generated by permanent magnets and electromagnets. With this hybrid magnetic field, the initial stiffness of the MRE joint can be designed to be hard so as to suppress the hunting motions and vibrations of wheelsets and thus keep the trains’ high-speed stability; furthermore, the stiffness can decrease by energizing the electromagnets when passing through a curve track. With this characteristic, the joint can guarantee the safety of the train at high operation speed even when the joint control system fails. The prototype of the MRE joint was fabricated and assembled. Stiffness controllability of the MRE joint was tested using an MTS machine. The result reveals that the stiffness of this MRE joint can be controlled effectively. According to the testing results, a new phenomenological model was built to predict the joint’s dynamic performance. Then this established model was integrated into dynamic models of trains to numerically evaluate the new joint’s influence on the train’s stability and trafficability. The evaluation result shows that the proposed MRE joint is fully effective on providing controllable stiffness to satisfy the conflicting stiffness requirement with fail-safe characteristics.

The Design of Intelligent Spray Painting System for Ship Panel Based on UAV

This paper proposes a new form of using UAVs to carry spray painting process equipment to spray outer plates of ships, which solves the paining points of poor practicality, poor versatility and low intelligence of existing robotic spray painting and has received wide attention from experts in the industry. It includes two types of hardware equipment and three software systems, among which the hardware equipment includes intelligent spray painting platform and material supply platform, and the software system includes intelligent planning system of spray painting path, intelligent spray painting stability control system and “double platform” dynamic joint control system. Through experimental verification, the intelligent spray painting system of ship outer plate based on UAV proposed in this paper realizes intelligent spray painting of ship outer plate, improves safety, economy and efficiency of ship outer plate spray painting, and further promotes intelligent transformation of ship construction and high-quality development of ship industry.

Fin-Rudder Joint Control Based on Improved Linear-Quadratic-Regulator Algorithm

Navigation accidents and disasters frequently occur when ships sail at sea due to extreme weather, wind, and wave conditions. The disturbance of wind and waves affects the stability of the ship’s course and makes the ship roll violently. Ships are usually equipped with an autopilot to control the course and a fin stabilizer to reduce rolling during navigation and improve stability and safety. Fin-rudder joint control system considers the coupling effect of the ship’s horizontal plane motion, thereby improving the performance of the rudder and the fin stabilizer. This paper presents an improved linear-quadratic-regulator control algorithm. A rate control law with no static error is proposed based on the traditional linear-quadratic regulator to eliminate the static error of the state vector and achieve a better control effect. Additionally, a closed-loop state observer is used to estimate the system’s state vector, and a dynamic corrector is designed to reduce rolling and heading angle deviation caused by sea wave interference. The simulation results show that the designed fin-rudder joint controller with the improved linear-quadratic regulator algorithm can achieve more than 80% roll reduction effect at level 3 and 5 sea states, and has better course keeping ability compared with the rudder control.

An Innovative Mechanism of Blockchain Technology on Joint Governance Model

Joint prevention and control is a social organization model dealing with the governance of public health and security incidents. The governance modelsshould have the features of multiple subjects co-governing and distributed cooperating. Their purposes are to solve and improve the governance efficiency of dealing with public health and security incidents at the executive level. However, there are still many deficiencies in the current data governance and collaborative governance of joint prevention and control systems, which are mainly reflected in incomplete data collection, unimpeded data sharing, inflexible collaborative cooperation, and inadequate collaborative supervision. Therefore, a new innovative governance model is urgently needed. Blockchain technology is suitable for implementing multi-party data sharing and cooperation, and at the same time, it supports penetrating supervision and management. This paper studies the blockchain model for joint governance of public health and security incidents. It focuses on the multi-agent collaborative prevention and control governance model, which provides a new opportunity for model innovation in data governance and in cooperative governance.

Study on the Construction of Water Environment Promotion Joint Control and Joint Regulation System in Plain River Network Area

There are many river networks in Southeast plain cities of China, such as dense river network, many water projects, poor connectivity, strong pollution load into the river, and difficulty in regulation and control. The water environment problem of river network has become the bottleneck restricting the sustainable economic and social development of plain river network area. In order to improve the river water environment, it is very important to carry out reasonable intelligent regulation of regional river system. In view of the current situation that the water environment regulation is mainly based on manual operation and has not formed intelligent dispatching decision-making, this paper integrates the technology of water power and water quality joint control of urban river network, researches and develops the joint control and joint dispatching system of water environment improvement in plain river network area, and establishes a full coverage, full element three-dimensional monitoring and warning, dispatching and intelligent decision-making system, driven by monitoring data, with model as the core and remote control as the core with the goal of hydrodynamic, water level and water quality as the target, relying on the model cloud, the intelligent one click precise scheduling is realized.

Analysis of Characteristics of Volatile Organic Compounds Pollution in Atmosphere in Kuitun City and Countermeasures

The "Kui-Du-Wu" area of Kuitun City is one of the largest petrochemical bases and important economic core areas in Xinjiang. According to the online monitoring data of total volatile organic compounds (VOCs) at Kuitun site, 102 species can be detected in the urban atmospheric environment volatile organic compounds, through the analysis of the sources of the top ten compounds with average concentration values throughout the year, their main sources are chemical production, oil volatilization, fuel combustion, and motor vehicle exhaust. The prevention and control countermeasures are to strengthen source control, implement pollution source compliance management, improve the city's comprehensive management level, and establish and improve a joint prevention and control system.

Collision Avoidance System Synthesis for a Group of Robots in Unsupervised Learning Paradigm

Collision avoidance is very important problem in the domain of multi-robot interaction. In this paper we propose a new approach of collision avoidance in the context of the optimal control system synthesis problem definition with minimal information available. It is assumed that robots have a certain scope within which they can interact with static and dynamic phase constraints. A group of robots is considered to be homogeneous, and control system unit for reaching terminal states already available to robots. The control system which is responsible for collision avoidance is only activated when the nearest neighbor is located in the scope of the considered robot. The first important feature of this work is the fact that the collision avoidance between two robots is reciprocal with joint control system, without assigning priorities. Another key feature of this work is the complete absence of information about the environment and the current state of other robots at given time. Robots only share information with nearest neighbors if they locate in the scope of each other. We also present a computational experiment with mobile robots as control objects. A multilayer perceptron was used to approximate the control function. Weights of the perceptron were optimized in unsupervised paradigm by an algorithm belonging to the evolutionary strategies class. At the beginning of each epoch we generate a sample of collision scenarios for optimization, while the quality criterion of the achieved weights at the end of epoch is evaluated on a fixed test sample. Experimental results demonstrate strong ability of the optimized multilayer perceptron to map the relative state of two mobile robots to controls in order to avoid collisions.

The challenges in implementing future interoperable joint C4ISR systems

AbstractThe unprecedented scale of ultra large scale (ULS) systems spans into various dimensions like lines of code, amount of information processed, number of interdependent hardware and computational components, number of people involved etc. The characteristics of ULS systems due to their scale pose different challenges which could only be addressed by a multi‐disciplinary research rather than the traditional software engineering approaches. In this paper, we focused on proposing solutions against challenges in implementing the future interoperable joint Command, Control, Communications, Computers, Intelligence, Surveillance and Reconnaissance (C4ISR) systems. For this purpose, we examined the main research topics to address the challenges in ULS systems. We discussed two main capabilities to enable the vision of future interoperable joint C4ISR. One of these capabilities is the effective and secure use of information across components of the system, while the other one is real‐time fusion of the available information with the local context.