Collaborative Control Research Articles

Research on collaborative adaptive cruise control based on MPC and improved spacing policy

A Cooperative Adaptive Cruise Control (CACC) algorithm based on Model Predictive Control (MPC) and an improved spacing policy is proposed in this study to address the current issues of low road utilization and inadequate dynamic regulation during platoon driving. First and foremost, the state of the leader vehicle and the minimum safe following distance are incorporated into the spacing policy to create an enhanced constant time headway (CTH) spacing policy. Secondly, following the MPC principle, the optimization problem of vehicle platoon is converted into a constrained quadratic programming problem that fulfills the requirements of driving safety, following distance, and ride comfort in a platoon. Finally, six-homogeneous-vehicle platoon is constructed for simulation verification, and the results show that the designed algorithm can not only ensure the string stability of platoon, but also effectively improve the road utilization rate. And in the vehicle of platoon cut-in/cut-out conditions, CACC is proven to have good ability of dynamically adjusting and restoring platoon stability.

Collaborative control of path tracking and roll stability in intelligent commercial vehicle: A minimax robust regulator based on Nash game

—Currently, most vehicles are generally equipped with roll stability control system or electronic stability control system to improve stability. However, when encountering emergency obstacle avoidance and similar conditions, roll stability control system may compete with path tracking control system for vehicle control, resulting in the inability to balance path tracking and roll stability. Therefore, a closed-loop feedback Nash game collaborative control method is proposed to solve the collaborative problem between the two control systems. Firstly, a fifth-order vehicle model with coupled yaw-roll dynamics is presented, which was extended to a vehicle-road closed-loop model based on lateral position, yaw angle and road preview information. Secondly, the path tracking control system and roll stability control system are regarded as two agents in the dynamic game control process. On this basis, a Nash game collaborative control strategy is designed by fully considering the control interaction between two game agents. Finally, considering the influence of uncertain disturbances, a finite-time minimax robust control strategy is proposed by using minimax optimization theory. Simulation and hardware in loop experiments show that the minimax robust regulator based on Nash game controller can effectively improve the path tracking and roll stability performance of vehicles. Moreover, the regulator improves the robustness of the system when it is subjected to bounded uncertain lateral disturbances.

Recent Developments in Crowd Management: Theory and Applications

Managing crowds is important not only during evacuation in disasters such as earthquakes and fires but also during normal situations. In particular, places where many people gather every day, such as stations or event venues, need such management to prevent crowd accidents. Moreover, efficient guidance that prevents people from waiting or queuing can improve facility services and lead to business opportunities. In this study, we propose a crowd management platform to prevent crowd accidents and provide efficient guidance to visitors. Specifically, we integrate real-time observations of crowd conditions, predictions, and risk assessments through simulation and crowd control in collaboration with security and facility managers. We also present the results of operating this platform in actual fields, which contribute to and support the safety and comfort of individuals.

Revealing the Contribution of Interfacial Processes to Atmospheric Oxidizing Capacity in Haze Chemistry.

The atmospheric oxidizing capacity is the most important driving force for the chemical transformation of pollutants in the atmosphere. Traditionally, the atmospheric oxidizing capacity mainly depends on the concentration of O3 and other gaseous oxidants. However, the atmospheric oxidizing capacity based on gas-phase oxidation cannot accurately describe the explosive growth of secondary particulate matter under complex air pollution. From the chemical perspective, the atmospheric oxidizing capacity mainly comes from the activation of O2, which can be achieved in both gas-phase and interfacial processes. In the heterogeneous or multiphase formation pathways of secondary particulate matter, the enhancement of oxidizing capacity ascribed to the O2/H2O-involved interfacial oxidation and hydrolysis processes is an unrecognized source of atmospheric oxidizing capacity. Revealing the enhanced oxidizing capacity due to interfacial processes in high-concentration particulate matter environments and its contribution to the formation of secondary pollution are critical in understanding haze chemistry. The accurate evaluation of atmospheric oxidizing capacity ascribed to interfacial processes is also an important scientific basis for the implementation of PM2.5 and O3 collaborative control in China and around the world.

A Collaborative Control Method of Transmission Amplitude and Phase for Transmitarray Antenna Design

In this paper, a collaborative control method of transmission amplitude and phase for transmitarray antenna (TA) design is proposed. In this proposed method, one of the most popular hypersurface fitting models, Gaussian stochastic process (GP) model, is utilized to construct an accurate surrogate model. Following this implementation, a mapping relationship between structural parameters of TA unit cell and its transmission amplitude and phase is established. The most advantage of this method is its applicability for general TA designs because it is much difficult to control the amplitude and phase of unit cell independently through adjusting separate structural parameters. To verify the high efficiency of the proposed method, three TA antennas with different scanning angles are designed to obtain high sidelobe suppression level. Measured results show that the proposed collaborative control method of amplitude and phase is much promising for high sidelobe suppression level in TA designs.

Enhanced Fine-Grained Motion Diffusion for Text-Driven Human Motion Synthesis

The emergence of text-driven motion synthesis technique provides animators with great potential to create efficiently. However, in most cases, textual expressions only contain general and qualitative motion descriptions, while lack fine depiction and sufficient intensity, leading to the synthesized motions that either (a) semantically compliant but uncontrollable over specific pose details, or (b) even deviates from the provided descriptions, bringing animators with undesired cases. In this paper, we propose DiffKFC, a conditional diffusion model for text-driven motion synthesis with KeyFrames Collaborated, enabling realistic generation with collaborative and efficient dual-level control: coarse guidance at semantic level, with only few keyframes for direct and fine-grained depiction down to body posture level. Unlike existing inference-editing diffusion models that incorporate conditions without training, our conditional diffusion model is explicitly trained and can fully exploit correlations among texts, keyframes and the diffused target frames. To preserve the control capability of discrete and sparse keyframes, we customize dilated mask attention modules where only partial valid tokens participate in local-to-global attention, indicated by the dilated keyframe mask. Additionally, we develop a simple yet effective smoothness prior, which steers the generated frames towards seamless keyframe transitions at inference. Extensive experiments show that our model not only achieves state-of-the-art performance in terms of semantic fidelity, but more importantly, is able to satisfy animator requirements through fine-grained guidance without tedious labor.

The synergy effect of energy security and carbon-haze collaborative management: From the perspective of biased technological progress

It is important to ensure energy security and achieve carbon-haze collaborative management for sustainable development. Reducing imported energy dependence is necessary to maintain energy security, while its impact on environmental quality remains unclear. From the perspective of biased technological progress, this paper estimates the level of biased technological progress towards self-sufficient energy by a heterogeneous stochastic frontier analysis (SFA) function, and then empirically examines whether self-sufficient energy biased technological progress has a dampening effect on haze pollution and carbon emissions. It is found that: (1) Self-sufficient energy biased technological progress can effectively reduce haze pollution and carbon emissions, achieving a synergistic effect between energy security and carbon-haze collaborative management. (2) “Efficiency enhancement” and “quality improvement” are the essential mechanisms for the synergistic effect. (3) Environmental regulation, abundant resource and technology endowments can enhance the haze reduction effect. And the lower dependence on foreign trade and stable global economic policy environment are more conducive to achieving carbon-haze collaborative control. (4) In the Eastern and Western regions, self-sufficient energy biased technology can be sped up to alleviate haze pollution. The findings can enrich the research exploring pollution control from the perspective of biased technological progress, and provide policy recommendations for promoting high-quality development.

Collaborative Control of Reactive Power and Voltage in a Coupled System Considering the Available Reactive Power Margin

This article proposes a hierarchical collaborative reactive power and voltage control method aimed at meeting the internal voltage requirements of a coupled system composed of centralized new energy stations such as wind and solar power and traditional thermal power units, with particular attention paid to the reactive power regulation ability of power units in new energy stations. This method is implemented in two layers: At the transmission layer, the overall reactive power compensation capacity of thermal power units and stations on the transmission lines within the system is determined according to the engineering requirements of different node voltages in the coupled system, the regulation voltages of the high-voltage grid-connected points and the point of common coupling (PCC) of the stations are found, and the actual regulation voltages of the PCCs of the stations are given as commands. At the station layer, based on determining reactive power distribution between power units and continuous reactive power compensation devices within each station, voltage optimization is carried out using the voltage command issued by the transmission layer as a reference. At the same time, consistency coordination between the transmission layer and the station layer is achieved based on the Analytical Target Cascading (ATC) method at different layers. Finally, simulation analysis was conducted on a regional coupled system in Dalian. The results showed that the method proposed in this paper can effectively control the voltage safety requirements of each region and PCC in the coupled system and, to some extent, improve the economic efficiency of system operation.

A Collaborative Control Framework: Achieving Emergency Vehicle Priority While Minimizing Negative Impact on Ordinary Vehicles at Signalized Intersection

When an emergency vehicle (EV) passes through an isolated signal intersection, it is crucial to ensure the efficient passage of the EV while minimizing the negative impact on ordinary vehicles (OVs), particularly in high-traffic flow scenarios. Given the constraints on temporal and spatial resources within intersection areas, OVs ahead of EV often face challenges in finding safe gaps for giving way, resulting in significant obstructions to OVs. This research introduces a novel collaborative control framework to jointly optimize dynamic emergency lane settings and signal schemes, considering EV priority and OVs benefits for a single signalized intersection. Firstly, we propose a dynamic emergency lane control algorithm to help obstructed EV in roadway segments by extending and reallocating temporal and spatial resources for vehicles. Then, we establish a collaborative control model considering EV priority and OVs benefits. Assigning the highest priority to the emergency priority phase, this model optimizes signal schemes to prevent interphase conflict, taking into account OVs benefits. Finally, our collaborative control framework also employs an Eco-Driving algorithm for the optimization of OV speed to reduce fuel consumption. The case study results reveal that in comparison to other baseline methods, our proposed model significantly reduces EV travel time, simultaneously lowering the travel time and fuel consumption of OVs. Sensitivity analysis of varying traffic flow scenarios reveals that, as vehicle volumes increase, our proposed method demonstrates more pronounced reductions in both EV and OV travel time. In addition, there is a progressive increase in the proportion of dynamic emergency lane utilization, with activation occurring at earlier locations.

Preparation of the close cross-section component of NiAl-based alloy by a novel combined sintering method

In this study, to overcome the bottleneck of forming NiAl for aerospace applications, a novel combined sintering method based on hot-press sintering, which divides the components into various parts and compacts them gradually, is proposed and studied. Two typical close cross-sectional components (tube-like components and conical tube components with flanges), which are highly demanding and more challenging to obtain for NiAl intermetallic, were prepared and analyzed in detail. Based on these results, both prepared components were fully dense. In addition, as shown by the bending tests, the interfacial strength is between the strengths of the base alloys on the two sides, which confirms the reliable bonding ability achieved by this method. For the conical tube component with flange, the ultimate tensile strength of the combined-sintered part in 1000 ℃ is 406.7±3.2 MPa, and the ultimate strength of the pre-sintered part is 368.6±2.7 MPa, which are 39% and 26% higher than the strength of blade-like component prepared by casting and hot isostatic pressing (292 MPa). The proposed method discussed in our study can overcome the uneven density defects in HPS and achieve collaborative control of both the shape and performance when preparing a high height-to-thickness ratio or a complex-shaped close cross-section component.

New insight into the intrinsic effect of sulfur dioxide on Hg0 oxidation in the absence/presence of SCR atmosphere

Collaborative control of Hg0 in selective catalytic reduction (SCR) device is considered to be feasible and cost-effective, whereas the negative impact of SO2 remains a thorny issue for industrial applications. Herein, the intrinsic effect mechanism of SO2 on Hg0 oxidation in the absence/presence of SCR atmosphere over the hollow nanotube CoMnTiOx was systematically investigated. It was demonstrated that SO2 possessed a bidirectional effect on Hg0 oxidation, the facilitating effect was attributed to the production of HgSO4 and the inhibiting effect was due to the formation of metal sulfate, which was exactly equilibrated when the deposition of sulfate on the catalyst reached 3.88 %. Interestingly, the presence of SCR atmosphere enhanced the suppression of SO2 on Hg0 oxidation, which was caused by the fact that SO2 + O2 consumed partial Hg0 to form HgSO4, upsetting the reaction equilibrium of HgO reduction induced by SCR atmosphere and ultimately aggravating the reduction process of the already generated HgO. This work provides a new and comprehensive insight into the effect of SO2 on Hg0 oxidation during the synergistic removal of Hg0 in SCR device, which is instructive in exploring strategies to mitigate the SO2 poisoning.

Absorption-transmission-diffusion-type radar cross section reduction metasurfaces based on frequency selective absorber and polarization conversion chessboard structure

Absorption-transmission-diffusion-type radar cross section (RCS) reduction metasurfaces based on the frequency selective absorber and the polarization conversion chessboard structure are proposed in this paper. The RCS reduction metasurfaces consist of three parts, i.e. the top layer realized by a cross-shaped meander line loaded with lumped resistors for low-frequency absorption and high-frequency transmission, the mid-layer constructed by angular ring vias frequency selective surface (FSS) sandwiched with two square patches FSS for broadband transmission in mid-frequency zone, and the bottom layer employed chessboard metasurfaces composed of dual-arrow type polarization conversion units for scattering cancellation in high frequency zone. The physical mechanisms of the RCS reduction metasurfaces with multifunctional electromagnetic controlling including wave absorption, bandpass transmission, polarization reversal, and phase cancellation are also discussed and analyzed. Simulation and experimental results demonstrate a reflection of lower than −10 dB for normal incident linearly polarized waves over a frequency range of 2.5 GHz–18 GHz, with a relative bandwidth of 151.22%; transmission passband properties with insertion loss better to −3 dB in the frequency range of 5.62 GHz–11.0 GHz, with a relative bandwidth of 64.74%. Due to the resonance-coupling-resonance principle, the broadband transmission with low insertion loss was obtained. The RCS properties of the proposed multi-functional metasurfaces were further analyzed by numerical simulation and experimental measurement, and the results showed that RCS reduction of over 10 dB was achieved for normal incident different polarized waves at the frequency range of 2.5 GHz to 17 GHz. Even in the case of normal incidence, there was a deviation between the reflection characteristics and RCS reduction. The RCS reduction metasurfaces are expected to be employed in applications where multi mechanism collaborative control of electromagnetic waves is of extreme importance.

Level of Community Participation in Development of Denai Lama Village Tourism Village

This research delves into the community participation in developing a tourism village in Denai Lama Village, Pantai Labu District. Employing quantitative methods and factor analysis on 85 samples, which includes pokdarwis officials and traders from Pasar Kamu and Paloh Naga, the study drew significant findings. The results indicate that manipulation, therapy, information, placement, collaboration, and citizen control significantly influence community participation. However, consultation and delegation factors showed lesser impact. There are both supporting and constraining elements affecting community involvement. Key enablers for active community participation include available opportunities, individual willingness, and capability to effectively engage. On the other hand, individual attributes and demographics, such as age, gender, and education level, can inhibit participation. The study highlights the vital role of government and institutional intervention in promoting community engagement in decision-making processes and in the execution of tourism village projects. For the Denai Lama Village, it's crucial to understand how human demographics may limit community involvement, guiding strategies to enhance active participation in future tourism village developments.

CVDMARL: A Communication-Enhanced Value Decomposition Multi-Agent Reinforcement Learning Traffic Signal Control Method

Effective traffic signal control (TSC) plays an important role in reducing vehicle emissions and improving the sustainability of the transportation system. Recently, the feasibility of using multi-agent reinforcement learning technology for TSC has been widely verified. However, the process of mapping road network states onto actions has encountered many challenges, due to the limited communication between agents and the partial observability of the traffic environment. To address this problem, this paper proposes a communication-enhancement value decomposition, multi-agent reinforcement learning TSC method (CVDMARL). The model combines two communication methods: implicit and explicit communication, decouples the complex relationships among the multi-signal agents through the centralized-training and decentralized-execution paradigm, and uses a modified deep network to realize the mining and selective transmission of traffic flow features. We compare and analyze CVDMARL with six different baseline methods based on real datasets. The results show that compared to the optimal method MN_Light, among the baseline methods, CVDMARL’s queue length during peak hours was reduced by 9.12%, the waiting time was reduced by 7.67%, and the convergence algebra was reduced by 7.97%. While enriching the information content, it also reduces communication overhead and has better control effects, providing a new idea for solving the collaborative control problem of multi-signalized intersections.

Revocable and verifiable weighted attribute-based encryption with collaborative access for electronic health record in cloud

The encryption of user data is crucial when employing electronic health record services to guarantee the security of the data stored on cloud servers. Attribute-based encryption (ABE) scheme is considered a powerful encryption technique that offers flexible and fine-grained access control capabilities. Further, the multi-user collaborative access ABE scheme additionally supports users to acquire access authorization through collaborative works. However, the existing multi-user collaborative access ABE schemes do not consider the different weights of collaboration users. Therefore, using these schemes for weighted multi-user collaborative access results in redundant attributes, which inevitably reduces the efficiency of the ABE scheme. This paper proposes a revocable and verifiable weighted attribute-based encryption with collaborative access scheme (RVWABE-CA), which can provide efficient weighted multi-user collaborative access, user revocation, and data integrity verification, as the fundamental cornerstone for establishing a robust framework to facilitate secure sharing of electronic health records in a public cloud environment. In detail, this scheme employs a novel weighted access tree to eliminate redundant attributes, utilizes encryption version information to control user revocation, and establishes Merkle Hash Tree for data integrity verification. We prove that our scheme is resistant against chosen plaintext attack. The experimental results demonstrate that our scheme has significant computational efficiency advantages compared to related works, without increasing storage or communication overhead. Therefore, the RVWABE-CA scheme can provide an efficient and flexible weighted collaborative access control and user revocation mechanism as well as data integrity verification for electronic health record systems.

Research on mine ventilation network solution and collaborative control technology

With the development of intelligent ventilation system in domestic coal mines, the demand for ventilation network solving software is becoming more and more intense. Aiming at the problem that the traditional ventilation network solution algorithm is difficult to meet the increasingly complex ventilation system solution needs of domestic mines, and the lack of functions of the collaborative control of ventilation equipment and facilities, this paper uses theoretical analysis combined with mine reality to study the relevant theories and algorithms in the field of ventilation network solution and collaborative control at home and abroad, and optimizes the network solution and collaborative control related algorithms such as iterative calculation of ventilation network, identification and stability analysis of angle-linked wind network, natural wind pressure calculation, local fan collaborative control, and collaborative control of damper and wind window. Provide theoretical guidance for future network solution software development.

Power Advance Prediction to Improve the Energy Utilization Efficiency of Motor-Driven System Considering Multilink Time-Delay

In the motor-driven system, the utilization of a supercapacitor energy storage unit contributes to energy saving. However, the multi-link time-delay in the system makes the supercapacitor unable to immediately track and respond to the sharp change of motor power. This will cause the large DC bus voltage fluctuation, the peak current at the power grid side, and unnecessary energy loss. In this paper, a power advance prediction control strategy considering multi-link time-delay is proposed. The multi-link time-delay mechanism in the system is analyzed, in particular for the different conditions of motor power change. Afterward, with the motor speed, torque, and the inverter acceleration/deceleration rate obtained in advance, the motor steady power and power change rate are predicted. In the dynamic process, by adjusting the tracking rate in real time, the motor reference power function is derived. The reference current of the supercapacitor is given online, so as to match the power between the motor and the energy storage unit. Both simulation and experimental results verify the rationality and validity of the proposed control strategy. In the dynamic process, the system stability and energy utilization are successfully improved in comparison with multi-parameter collaborative power prediction control and double closed-loop control.

An Economic Model Predictive Control for Knowledge Transmission Processes in Multilayer Complex Networks.

In this article, we study the optimal feedback control problems of knowledge dissemination processes in multilayer complex networks. First, a node-based model is established in multilayer complex networks and two collaborative control strategies are exerted to increase the scope and speed of knowledge dissemination, forming a closed-loop control system. Then, we develop a two-layer optimal control framework. At the upper level, the optimal solution of the control system is solved and sent to the lower layer. At the lower level, a model predictive controller (MPC) receives input information from the upper level and is formulated to decide on the network and then transmits it to its heterogeneous networks which can reduce control resources and computation complexity. Finally, numerical simulations are conducted to confirm the theoretical results.

Effects of blockchain technology (BT) on the university librarians and libraries: a systematic literature review (SLR)

PurposeThe objectives of the study were to identify the effects of blockchain technology (BT) on the university librarians, the impact of BT on the university library services and to reveal the challenges to adopt BT in the university libraries.Design/methodology/approachA systematic literature review was applied to address the objectives of the study. Around 25 studies published in peer-reviewed journals were selected to conduct the study.FindingsThe findings of the study revealed that blockchain technology (BT) has positive effects on the university librarians as it assists them in digital resources management, provision of integrated library services, effective records management and continued professional development. The study also displayed that BT has a positive impact on the university libraries through effective information management, user privacy, collaboration, technological innovation and access control. Results also revealed that technical issues, financial constraints, security problems, skill issues and sociocultural issues created challenges to adopt BT in the university libraries.Originality/valueThe study has offered theoretical implications for future investigators through the provision of innovative literature on the prospectus and challenges associated with blockchain in the context of librarianship. The study has also provided practical implications for management bodies by offering recommendations for the successful adoption of blockchain in the university libraries. Additionally, a framework has been developed to adopt BT successfully in the university libraries for the delivery of smart library services to library patrons.

Resource-aware multi-criteria vehicle participation for federated learning in Internet of vehicles

Federated learning (FL), as a safe distributed training mode, provides strong support for the edge intelligence of the Internet of Vehicles (IoV) to realize efficient collaborative control and safe data sharing. However, due to the resource limitation and the instability of training environment in the complex IoV, ideal performance of FL cannot be achieved. Since considering the actual resource constraints and federated task requirements, the diversified device selection criteria make the resource-aware vehicle selection problem become a multi-criteria selection problem. To effectively support FL for IoV, the resource-aware multi-criteria vehicle selection problem was described as a many-objective optimization problem, and a resource-aware many-objective vehicle selection model (RA-MaOVSM) is proposed to optimize resource efficiency. The RA-MaOVSM considering heterogeneous resources (like computation resources, communication resources, energy resources and data resources) of on-board devices in IoV, and realizes the joint optimization of learning efficiency, energy cost and global performance. Additionally, a novel probability distribution combination game strategy is applied to many-objective evolutionary algorithm (MaOEA) for improving the model solving performance. Simulation results demonstrate that RA-MaOVSM can effectively optimize the IoV resources and FL model performance, and the designed algorithm exhibits good convergence and distribution, achieving a good balance among multiple device selection criteria.