Network Topology Connection Optimization Control Algorithm Based on Network Efficiency and Average Connectivity

2014 ◽  
Vol 9 (5) ◽  
Author(s):  
Xianwang Li ◽  
Yuchuan Song ◽  
Ping Yan ◽  
Xuehai Chen
2021 ◽  
Vol 12 (3) ◽  
pp. 107
Author(s):  
Tao Chen ◽  
Peng Fu ◽  
Xiaojiao Chen ◽  
Sheng Dou ◽  
Liansheng Huang ◽  
...  

This paper presents a systematic structure and a control strategy for the electric vehicle charging station. The system uses a three-phase three-level neutral point clamped (NPC) rectifier to drive multiple three-phase three-level NPC converters to provide electric energy for electric vehicles. This topology can realize the single-phase AC mode, three-phase AC mode, and DC mode by adding some switches to meet different charging requirements. In the case of multiple electric vehicles charging simultaneously, a system optimization control algorithm is adopted to minimize DC-bus current fluctuation by analyzing and reconstructing the DC-bus current in various charging modes. This algorithm uses the genetic algorithm (ga) as the core of computing and reduces the number of change parameter variables within a limited range. The DC-bus current fluctuation is still minimal. The charging station system structure and the proposed system-level optimization control algorithm can improve the DC-side current stability through model calculation and simulation verification.


2011 ◽  
Vol 317-319 ◽  
pp. 1373-1384 ◽  
Author(s):  
Juan Chen ◽  
Chang Liang Yuan

To solve the traffic congestion control problem on oversaturated network, the total delay is classified into two parts: the feeding delay and the non-feeding delay, and the control problem is formulated as a conflicted multi-objective control problem. The simultaneous control of multiple objectives is different from single objective control in that there is no unique solution to multi-objective control problems(MOPs). Multi-objective control usually involves many conflicting and incompatible objectives, therefore, a set of optimal trade-off solutions known as the Pareto-optimal solutions is required. Based on this background, a modified compatible control algorithm(MOCC) hunting for suboptimal and feasible region as the control aim rather than precise optimal point is proposed in this paper to solve the conflicted oversaturated traffic network control problem. Since it is impossible to avoid the inaccurate system model and input disturbance, the controller of the proposed multi-objective compatible control strategy is designed based on feedback control structure. Besides, considering the difference between control problem and optimization problem, user's preference are incorporated into multi-objective compatible control algorithm to guide the search direction. The proposed preference based compatible optimization control algorithm(PMOCC) is used to solve the oversaturated traffic network control problem in a core area of eleven junctions under the simulation environment. It is proved that the proposed compatible optimization control algorithm can handle the oversaturated traffic network control problem effectively than the fixed time control method.


2014 ◽  
Vol 933 ◽  
pp. 343-347
Author(s):  
Guo Qing Zhou ◽  
Lei Li

In order to solve control puzzle of complicated characteristics for complex industrial object, the paper proposed an intelligent control strategy. First it made the anatomy and pointed out that the conventional control strategy is unsuitable to control the complex process. Based on comparison among control strategies, first it made decomposition and coordination for complex process, and then selected intelligence based control strategies, finally adopted human simulation intelligence based control algorithm to implement the optimization control of complex process with uncertainty. The simulation effect demonstrated that it is faster in response, high in control accuracy, and strong in robustness. The simulation shows that it is a wise choice to apply the intelligent control strategy for complex industrial process with uncertainty.


Author(s):  
Yanjie Zhang ◽  
Yalda Saadat ◽  
Dongming Zhang ◽  
Bilal M. Ayyub ◽  
Hongwei Huang

With the degradation of metrorail facilities and the increase in network size, it is urgently needed to perform vulnerability assessment to ensure the safe operation of the metro system. In this paper, a link-weighted network model is proposed by considering the physical interval length between neighboring metro stations as link weight factor. Firstly, the metro network was essentially mapped into a bipartite topological diagram that consists of nodes denoting metro stations and links representing metro routes including any tunnels or bridges. After analyzing the network for its complexity level, it was revealed that the metro network topology can be appropriately constructed by using the Space L method. On this basis, multiple characteristic indexes of the network were calculated to characterize network topology structural features. We then tested the state of Shanghai metro network under different failure scenarios by removing a fraction of nodes from the network. Quantitative vulnerability analyses were conducted according to the change in the topological structure of Shanghai metro network and the change in the corresponding global network efficiency due to disruptions. Finally, both the network efficiency of link-weighted and unweighted Shanghai metro network topology were calculated and compared. This study has identified the vulnerable metro stations, which could provide support for the reasonable resource allocation of maintenance work and the decision-making in emergency treatment after failure. In order to increase the adaptability to emergencies and improve the operational efficiency, it was proposed that during the planning, construction, and operation of the metro system, the management and protection of the vulnerable stations should be given increased attention.


2016 ◽  
Vol 12 (10) ◽  
pp. 76
Author(s):  
Huarui Wu ◽  
Li Zhu

<p style="margin: 0in 0in 10pt;"><span style="font-family: Times New Roman; font-size: small;">Topology control is of great significance to reduce energy consumption of wireless sensor network nodes and prolong network lifetime. Different tasks taken by nodes may lead to node failures and fractures of data transmission links, hence undermining the overall network performance. In response to such problems, this paper presents a network topology control algorithm based on mobile nodes that fully considers node energy, node degree and network connectivity. Furthermore, a topology control model is established to analyze weak network topology areas and carry out local topology refactoring. Finally, a simulation experiment demonstrates that the presented algorithm is advantageous in balanced network energy consumption and network connectivity.</span></p>


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