Mathematical Modeling and Control Algorithm Development for Bidirectional Power Flow in CCS-CNT System

As the demand for more efficient and adaptable power distribution systems intensifies, especially in rural areas, innovative solutions like the Capacitor-Coupled Substation with a Controllable Network Transformer (CCS-CNT) are becoming increasingly critical. Traditional power distribution networks, often limited by unidirectional flow capabilities and inflexibility, struggle to meet the complex demands of modern energy systems. The CCS-CNT system offers a transformative approach by enabling bidirectional power flow between high-voltage transmission lines and local distribution networks, a feature that is essential for integrating renewable energy sources and ensuring reliable electrification in underserved regions. This paper presents a detailed mathematical representation of power flow within the CCS-CNT system, emphasizing the control of both active and reactive power through the adjustment of voltage levels and phase angles. A control algorithm is developed to dynamically manage power flow, ensuring optimal performance by minimizing losses and maintaining voltage stability across the network. The proposed CCS-CNT system demonstrates significant potential in enhancing the efficiency and reliability of power distribution, making it particularly suited for rural electrification and other applications where traditional methods fall short. The findings underscore the system's capability to adapt to varying operational conditions, offering a robust solution for modern power distribution challenges.

Group Hybrid Coordination Control of Multi-Agent Systems With Time-Delays and Additive Noises

A new kind of group coordination control problemgroup hybrid coordination control is investigated in this paper.The group hybrid coordination control means that in a whole multi-agent system(MAS)that consists of two subgroups with communications between them,agents in the two subgroups achieve consensus and containment,respectively.For MASs with both time-delays and additive noises,two group control protocols are proposed to solve this problem for the containment-oriented case and consensus-oriented case,respectively.By developing a new analysis idea,some sufficient conditions and necessary conditions related to the communication intensity betw een the two subgroups are obtained for the following two types of group hybrid coordination behavior:1)Agents in one subgroup and in another subgroup achieve weak consensus and containment,respectively;2)Agents in one subgroup and in another subgroup achieve strong consensus and containment,respectively.It is revealed that the decay of the communication impact betw een the two subgroups is necessary for the consensus-oriented case.Finally,the validity of the group control results is verified by several simulation examples.

Tracking Control of Multi-Agent Systems Using a Networked Predictive PID Tracking Scheme

With the rapid development of network technology and control technology,a networked multi-agent control system is a key direction of modern industrial control systems,such as industrial Internet systems.This paper studies the tracking control problem of networked multi-agent systems with communication constraints,where each agent has no information on the dynamics of other agents except their outputs.A networked predictive proportional integral derivative(PPID)tracking scheme is proposed to achieve the desired tracking performance,compensate actively for communication delays,and simplify implementation in a distributed manner.This scheme combines the past,present and predictive information of neighbour agents to form a tracking error signal for each agent,and applies the proportional,integral,and derivative of the agent tracking error signal to control each individual agent.The criteria of the stability and output tracking consensus of multi-agent systems with the networked PPID tracking scheme are derived through detailed analysis on the closed-loop systems.The effectiveness of the networked PPID tracking scheme is illustrated via an example.

Step-coordination Algorithm of Traffic Control Based on Multi-agent System

Aiming at the deficiency of conventional traffic control method, this paper proposes a new method based on multi-agent technology for traffic control. Different from many existing methods, this paper distinguishes traffic control on the basis of the agent technology from conventional traffic control method. The composition and structure of a multi-agent system （MAS） is first discussed. Then, the step-coordination strategies of intersection-agent, segment-agent, and area-agent are put forward. The advantages of the algorithm are demonstrated by a simulation study.

Improved Voltage Control Strategy for Photovoltaic Grid-Connected System Based on DoubleLayer Coordination Control

An improved automatic voltage coordination control strategy （AVCCS） based on ;automatic voltage control （AVC） and battery energy storage control （BESC） is proposed for photovoltaic grid-connected system （PVGS） to mitigate the voltage fluctuations caused by environmental disturbances. Only AVC is used when small environ- mental disturbances happen, while BESC is incorporated with AVC to restrain the voltage fluctuations when large disturbances happen. An adjustable parameter determining the allowed amplitudes of voltage fluctuations is introduced to realize the above switching process. A benchmark low voltage distribution system including ]？VGS is established by using the commercial software Dig SILENT. Simulation results show that the voltage under AVCCS satisfies the IEEE Standard 1547, and the installed battery capacity is also reduced. Meanwhile, the battery＇s service life is ex- tended by avoiding frequent charges/discharges in the control process.

A New Design of Robust H∞Load-Frequency Controller for Optimal Coordination of Energy Generation in Power System Stability Using LMI Approach

This paper presents the problem of robust H∞?load frequency controller design and robust H￥ based approach called advanced frequency control (AFC). The objective is to split the task of balancing frequency deviations introduced by renewable energy source (RES) and load variations according to the capabilities of storage and generators. The problem we address is to design an output feedback controller such that, all admissible parameter uncertainties, the closed-loop system satisfies not only the prespecified H∞? norm constraint on the transfer function from the disturbance input to the system output. The conventional generators mainly balance the low-frequency components and load variations while the energy storage devices compensate the high- frequency components. In order to enable the controller design for storage devices located at buses with no generators, a model for the frequency at such a bus is developed. Then, AEC controllers are synthesized through decentralized static output feedback to reduce the complexity. The conditions for the existence of desired controllers are derived in terms of a linear matrix inequality (LMI) algorithm is improved. From the simulation results, the system responses with the proposed controller are the best transient responses.

Adaptive signal control and coordination for urban traffic control in a connected vehicle environment: A review

Existing signal control systems for urban traffic are usually based on traffic flow data from fixed location detectors.Because of rapid advances in emerging vehicular communication,connected vehicle(CV)-based signal control demonstrates significant improvements over existing conventional signal control systems.Though various CV-based signal control systems have been investigated in the past decades,these approaches still have many issues and drawbacks to overcome.We summarize typical components and structures of these existing CV-based urban traffic signal control systems and digest several important issues from the summarized vital concepts.Last,future research directions are discussed with some suggestions.We hope this survey can facilitate the connected and automated vehicle and transportation research community to efficiently approach next-generation urban traffic signal control methods and systems.

Intelligent Sensing and Control of Road Construction Robot Scenes Based on Road Construction

Automatic control technology is the basis of road robot improvement,according to the characteristics of construction equipment and functions,the research will be input type perception from positioning acquisition,real-world monitoring,the process will use RTK-GNSS positional perception technology,by projecting the left side of the earth from Gauss-Krueger projection method,and then carry out the Cartesian conversion based on the characteristics of drawing;steering control system is the core of the electric drive unmanned module,on the basis of the analysis of the composition of the steering system of unmanned engineering vehicles,the steering system key components such as direction,torque sensor,drive motor and other models are established,the joint simulation model of unmanned engineering vehicles is established,the steering controller is designed using the PID method,the simulation results show that the control method can meet the construction path demand for automatic steering.The path planning will first formulate the construction area with preset values and realize the steering angle correction during driving by PID algorithm,and never realize the construction-based path planning,and the results show that the method can control the straight path within the error of 10 cm and the curve error within 20 cm.With the collaboration of various modules,the automatic construction simulation results of this robot show that the design path and control method is effective.

Interaction and coordinated development between desertification control and social economy in Xizang,China

Based on the general requirements of the coordinated development of"ecological livable"and"affluent life"in the rural revitalization strategy,the evaluation index system of desertification control was constructed,the interaction between desertification control and regional social economy and the internal space-time coordination mechanism were explored,and the quality of desertification control and its coordination degree with regional economic development were quantitatively analyzed.The decoupling mechanism of desertification governance society economy system were analyzed,and the high level for the government to promote desertification governance,constructing ecological economy coordinated development pattern to provide decision basis to Xizang desertification governance-social economic system interaction and coupling coordination development as the research object,introducing the coupling decoupling model to measure the coupling coordination model and system coordination and decoupling decoupling.Desertification control in Xizang shows a trend of gradual improvement,but the overall level is still not high and there is a lot of room for optimization.The coupling coordination degree of desertification control-social and economic system is in a steady fluctuation trend,rising from D value less than 0.55 in 2004 to 0.87 in 2018,in a state of coordinated development(good),and grey prediction analysis shows that D value is in a continuous rise.The coupling coordination degree of the six prefecture-level cities in Xizang and Ngari region is different in time and space,but the overall development trend is coordinated.The development index of desertification control and the socio-economic development index show the interaction of strong decoupling,strong negative decoupling and weak decoupling,and there are interaction effects of desertification control,economic development and social development at different scales.

Optimal design of coordination control strategy for distributed generation system

This paper presents a novel design procedure for optimizing the power distribution strategy in distributed generation system. A coordinating controller, responsible to distribute the total load power request among multiple DG units, is suggested based on the conception of hierarchical control structure in the dynamic system. The optimal control problem was formulated as a nonlinear optimization problem subject to set of constraints. The resulting problem was solved using the Kuhn-Tucker method. Computer simulation results demonstrate that the proposed method can provide better efficiency in terms of reducing total costs compared to existing methods. In addition, the proposed optimal load distribution strategy can be easily implemented in real-time thanks to the simplicity of closed-form solutions.

Application of a compound controller based on fuzzy control and support vector machine to ship's boiler-turbine coordinated control system

Multivariables, strong coupling, nonlinearity, and large delays characterize the boiler-turbine coordinated control systems for ship power equipment. To better deal with these conditions, a compound control strategy based on a support vector machine （SVM） with inverse identification was proposed and applied to research simulating coordinated control systems. This method combines SVM inverse control and fuzzy control, taking advantage of the merits of SVM inverse controls which can be designed easily and have high reliability, and those of fuzzy controls, which respond rapidly and have good anti-jamming capability and robustness. It ensures the controller can be controlled with near instantaneous adjustments to maintain a steady state, even if the SVM is not trained well. The simulation results show that the control quality of this fuzzy-SVM compound control algorithm is high, with good performance in dynamic response speed, static stability, restraint of overshoot, and robustness.

MODEL FOR CHAOS CONTROL OF REGIONAL Ec-R-Ev SYSTEM

In order to realize the coordination oriented management of the economy resource environment(Ec R Ev) composite system,its optimal aggregate coordinating measurement model is established.A self learning method is presented,which combines the optimizing technology and stability analysis together to achieve a tradeoff between the optimizing objective and system stability.So a model for chaos control of the composite system based on coordination is proposed.

FUZZY COORDINATION AND FORCE/POSITION CONTROL OF ROBOTIC MANIPULATOR

It is crucial for implementing force/position control of robotic manipulator under the constraint of unknown environment to determine the force control and the position control directions. This paper presents an on line algorithm to real timely estimate the tangent and the normal vectors of the constraint surface based on the measured contact force under the consideration of frictional force. A fuzzy synthesis policy is proposed to coordinate the conflict between the compliant force control and the stiff position control. An experimental study on an AdeptThree, a SCARA type robotic manipulator, is conducted. The experimental results show that the policy presented in the paper is effective.

Application of Large-Scale Systems Theory in Fire Control Systems

According the to the model of single tank fire control system, this paper makes use of decomposition-coordination theory of large-scale systems to discuss the shooting problem of multiple tank the control systems, and alalyzes specifically the three-tank the control systems and models.the process was imitated in computer, and the optimal shooting element of 3TS system was got. In addition, probability of hitting the target was calculated.

Research on Distributed Coordination Control Method for Microgrid System Based on Finite-time Event-triggered Consensus Algorithm

Microgrids are networked control systems with multiple distributed generators(DGs).Microgrids are associated with many problems,such as communication delays,high sampling rates,and frequent controller updates,which make it challenging to realize coordination control among the DGs.Therefore,finite-time consensus algorithms and event-triggered control methods are combined to propose a distributed coordination control method for microgrid systems.The DG in the microgrid system serves as an agent node in the control network,and a distributed secondary controller is designed using finite-time consensus algorithm,such that the frequency and voltage restoration control has a faster convergence time and better anti-interference performance.The event-triggered function was designed based on the state information of the agents.The controller exchanges the state information at the trigger instants.System stability is analyzed using the Lyapunov stability theory,and it is verified that the controller cannot exhibit the Zeno phenomenon in the event-triggered process.A simulation platform was developed in Matlab/Simulink to verify that the proposed control method can effectively reduce the frequency of controller updates during communication delays and the burden on the communication network.

State coordinated voltage control in an active distribution network with on-load tap changers and photovoltaic systems

Decreasing costs and favorable policies have resulted in increased penetration of solar photovoltaic(PV)power generation in distribution networks.As the PV systems penetration is likely to increase in the future,utilizing the reactive power capability of PV inverters to mitigate voltage deviations is being promoted.In recent years,droop control of inverter-based distributed energy resources has emerged as an essential tool for use in this study.The participation of PV systems in voltage regulation and its coordination with existing controllers,such as on-load tap changers,is paramount for controlling the voltage within specified limits.In this work,control strategies are presented that can be coordinated with the existing controls in a distributed manner.The effectiveness of the proposed method was demonstrated through simulation results on a distribution system.

Finite-time coordination control for formation flying spacecraft

This paper investigates a distributed coordination control scheme using an adaptive terminal sliding mode for formation flying spacecraft with coupled attitude and translational dynamics. In order to overcome the singularity of the traditional fast terminal sliding manifold, a novel fast terminal sliding manifold is given. And then, based on the adaptive control method, a continuous robust coordinated controller is designed to compensate external disturbances and to alleviate the chattering phenomenon. The theoretical analysis shows that the coordinated controller can guarantee the finite-time stability of the overall closed-loop system through local information exchange, and numerical simulations also demonstrate its effectiveness.

Coordinated control of coastal multi-source multi-load system with desalination load: a review

Traditional seawater desalination requires high amounts of energy, with correspondingly high costs and limited benefits, hindering wider applications of the process. To further improve the comprehensive economic benefits of seawater desalination, the desalination load can be combined with renewable energy sources such as solar energy, wind energy, and ocean energy or with the power grid to ensure its effective regulation. Utilizing energy internet(EI) technology, energy balance demand of the regional power grid, and coordinated control between coastal multi-source multi-load and regional distribution network with desalination load is reviewed herein. Several key technologies, including coordinated control of coastal multi-source multi-load system with seawater desalination load, flexible interaction between seawater desalination and regional distribution network, and combined control of coastal multi-source multi-load storage system with seawater desalination load, are discussed in detail. Adoption of the flexible interaction between seawater desalination and regional distribution networks is beneficial for solving water resource problems, improving the ability to dissipate distributed renewable energy, balancing and increasing grid loads, improving the safety and economy of coastal power grids, and achieving coordinated and comprehensive application of power grids, renewable energy sources, and coastal loads.

Predictive cruise control for heavy trucks based on slope information under cloud control system

With the advantage of fast calculation and map resources on cloud control system(CCS), cloud-based predictive cruise control(CPCC) for heavy trucks has great potential to improve energy efficiency, which is significant to achieve the goal of national carbon neutrality. However, most investigations focus on the on-board predictive cruise control(PCC) system,lack of research on CPCC architecture under CCS. Besides, the current PCC algorithms have the problems of a single control target and high computational complexity, which hinders the improvement of the control effect. In this paper, a layered architecture based on CCS is proposed to effectively address the realtime computing of CPCC system and the deployment of its algorithm on vehicle-cloud. In addition, based on the dynamic programming principle and the proposed road point segmentation method(RPSM), a PCC algorithm is designed to optimize the speed and gear of heavy trucks with slope information. Simulation results show that the CPCC system can adaptively control vehicle driving through the slope prediction, with fuel-saving rate of 6.17% in comparison with the constant cruise control. Also,compared with other similar algorithms, the PCC algorithm can make the engine operate more in the efficient zone by cooperatively optimizing the gear and speed. Moreover, the RPSM algorithm can reconfigure the road in advance, with a 91% roadpoint reduction rate, significantly reducing algorithm complexity.Therefore, this study has essential research significance for the economic driving of heavy trucks and the promotion of the CPCC system.

Coordination Control of Greenhouse Environmental Factors

Optimal control of greenhouse climate is one of the key techniques in digital agriculture.Greenhouse climate,a nonlinear and uncertain system,consists of several major environmental factors such as temperature,humidity,light intensity,and CO 2 concentration.Due to the complex coupled correlations,it is a challenge to achieve coordination control of greenhouse environmental factors.This paper proposes a model-free coordination control approach for greenhouse environmental factors based on Q-learning.Coordination control policy is found through systematic interaction with the dynamic environment to achieve optimal control for greenhouse climate with the control cost constraints.In order to decrease systematic trial-and-error risk and reduce the computational complexity in Q-learning algorithm,case-based reasoning （CBR） is seamlessly incorporated into the Q-learning process.The experimental results demonstrate that this approach is practical,highly effective and efficient.