scholarly journals Artificial Intelligence Based Sensor Network Congestion Fuzzy Control Algorithm

2021 ◽  
Vol 2074 (1) ◽  
pp. 012030
Author(s):  
Jing Luo ◽  
Xiaoxu Xiao ◽  
Rongxia Wang
Keyword(s):  
Artificial Intelligence ◽  
Sensor Networks ◽  
Fuzzy Control ◽  
Sensor Network ◽  
Control Algorithm ◽  
Large Scale ◽  
Cluster Head ◽  
Residual Energy ◽  
Congestion Control Algorithm ◽  
Fuzzy Control Algorithm

Abstract The topology control of sensor sensor network was studied based on fuzzy control algorithm. Aiming at the dynamic changes of the topology of large-scale and heterogeneous artificial intelligence sensor networks and the incomplete information between nodes, a smart network-based congestion control algorithm for sensor networks was proposed and the performance of fuzzy control algorithms was analyzed. Based on this, a fuzzy control algorithm was designed. The algorithm fully considered the residual energy of nodes and the distribution of nodes in the network. Therefore, the reasonable election of the cluster head can be realized through the game between nodes, which effectively avoided energy holes, made the network energy consumption more uniform, prolonged the network life cycle, and optimized the network topology.

scholarly journals Fault Location Measurement of Sensor Nodes based on Fuzzy Control Algorithm

2021 ◽  
Author(s):  
Nuo Yu
Keyword(s):  
Fuzzy Control ◽  
Measurement Method ◽  
Control Algorithm ◽  
Fault Location ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Cluster Member ◽  
Cluster Heads ◽  
Fuzzy Control Algorithm ◽  
Location Measurement

Abstract Aiming at the problems of the traditional fault location measurement method for sensor nodes, such as more energy consumption and longer measurement time, a fault location measurement method for sensor nodes based on fuzzy control algorithm is designed and proposed. First of all, the fuzzy control algorithm is analyzed; then the clustering based on cluster head diagnosis is carried out for the network, that is, the nodes that meet the cluster head conditions and are set as normal cluster heads are selected as cluster heads. Finally, combined with the fuzzy control algorithm, the fault location of each cluster member node is measured directly by cluster head nodes. The simulation results show that the proposed method has good performance.

scholarly journals Improvement of CH election in three-level heterogeneous WSN

2019 ◽  
Vol 13 (1) ◽  
pp. 272
Author(s):  
Jong-Yong Lee ◽  
Daesung Lee
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Cluster Head ◽  
Residual Energy ◽  
Initial Energy ◽  
Wireless Sensor ◽  
Increase Energy Efficiency ◽  
Leach Protocol ◽  
Long Time

<p>A Wireless Sensor Network is a wirelessly configured Sensor Node with limited power such as a battery. There are many Wireless Sensor Network Protocols to increase energy efficiency, among which LEACH Protocol and SEP are typical. The LEACH Protocol is mainly used for homogeneous sensor networks with the same initial energy, and SEP is used for heterogeneous sensor networks with different initial energies. In the case of SEP-E, another heterogeneous sensor with different initial energy is added. SEP and SEP-E provide a higher probability of Cluster Head election for node types with more energy than Normal Nodes. Since the current residual energy of the node is not confirmed, even if the energy is low, the Cluster Head may be elected because of the node type. In this paper, considering the residual energy of a node when a Cluster Head is elected, we increase the probability of electing a Cluster Head with more residual energy. Cluster Head consumes a lot of energy. A node with a lot of residual energy is elected as a Cluster Head, so the network lifetime can be used for a long time.</p>

Researches on the Robot Obstacle Avoidance Based on Fuzzy Control

2014 ◽  
Vol 686 ◽  
pp. 101-104
Author(s):  
Jin Yao
Keyword(s):  
Artificial Intelligence ◽  
Fuzzy Control ◽  
Obstacle Avoidance ◽  
Computer Technology ◽  
Control Algorithm ◽  
Biological Behavior ◽  
Sensor Technology ◽  
Covered Area ◽  
Local Path ◽  
Fuzzy Control Algorithm

With the continuous development of modern sensor technology, coupled with the integration of artificial intelligence and a variety of emerging computer technology, it makes robots more intelligent and diverse. So the ability of the robot to complete the task is also valued and widely used. In this paper, the whole covered area of the local path planning uses a fuzzy control algorithm, which uses the robustness and an action of perception based on the biological behavior of the fuzzy control algorithm combined with itself. For obstacle avoidance system of mobile robots, we put forward the avoidance strategy of fully contacting the obstacles. And we have conducted a deep study about the theory and implementation methods.

A Secure Cluster Head Selection Mechanism Based on Node's Features and Behavior in Wireless Sensor Networks

2019 ◽  
Vol 13 (3) ◽  
pp. 74-90
Author(s):  
Deepika Agrawal ◽  
Sudhakar Pandey ◽  
Veena Anand
Keyword(s):  
Sensor Networks ◽  
Sensor Network ◽  
Cluster Head ◽  
Residual Energy ◽  
Data Consistency ◽  
Primary Concern ◽  
Energy Distance ◽  
Iot Devices ◽  
And Behavior ◽  
The Internet Of Things

Security is the utmost importance for the safe operation of the Internet of Things (IoT) devices. Behind IoT, a sensor network operates. Hence, security and lifetime extensions of the sensor networks are the primary concern. Node clustering is a technique to lengthen the lifetime of sensor networks. In a clustering technique, Cluster Heads (CH) are chosen. To provide the security to the sensor network, reliable CHs are elected. In this article, a protocol is proposed which elects reliable CHs based on node features such as residual energy, distance to the sink and node behavior such as the number of packets transmitted and received successfully, data consistency factor. The simulation results obtained prove that the proposed protocol performs better.

Developing Multi-Tier Network Design for Effective Energy Consumption of Cluster Head Selection in WSN

2016 ◽  
Vol 13 (1) ◽  
pp. 116
Author(s):  
Wan Isni Sofiah Wan Din ◽  
Saadiah Yahya ◽  
Mohd Nasir Taib ◽  
Ahmad Ihsan Mohd Yassin ◽  
Razulaimi Razali
Keyword(s):  
Sensor Network ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Cluster Head Selection ◽  
Energy Usage ◽  
Network Cluster ◽  
Fuzzy Logic Approach ◽  
The Stability

Clustering in Wireless Sensor Network (WSN) is one of the methods to minimize the energy usage of sensor network. The design of sensor network itself can prolong the lifetime of network. Cluster head in each cluster is an important part in clustering to ensure the lifetime of each sensor node can be preserved as it acts as an intermediary node between the other sensors. Sensor nodes have the limitation of its battery where the battery is impossible to be replaced once it has been deployed. Thus, this paper presents an improvement of clustering algorithm for two-tier network as we named it as Multi-Tier Algorithm (MAP). For the cluster head selection, fuzzy logic approach has been used which it can minimize the energy usage of sensor nodes hence maximize the network lifetime. MAP clustering approach used in this paper covers the average of 100Mx100M network and involves three parameters that worked together in order to select the cluster head which are residual energy, communication cost and centrality. It is concluded that, MAP dominant the lifetime of WSN compared to LEACH and SEP protocols. For the future work, the stability of this algorithm can be verified in detailed via different data and energy. 

Space robot motion path planning based on fuzzy control algorithm

2021 ◽  
pp. 1-8
Author(s):  
Baoyu Shi ◽  
Hongtao Wu
Keyword(s):  
Path Planning ◽  
Fuzzy Control ◽  
Obstacle Avoidance ◽  
Control Algorithm ◽  
Space Robot ◽  
Robot Motion ◽  
Robot Path Planning ◽  
Behavior Based ◽  
Fuzzy Control Algorithm ◽  
Robot Path

Path planning technology is one of the core technologies of intelligent space robot. Combining image recognition technology and artificial intelligence learning algorithm for robot path planning in unknown space environment has become one of the hot research issues. The purpose of this paper is to propose a spatial robot path planning method based on improved fuzzy control, aiming at the shortcomings of path planning in the current industrial space robot motion control process, and based on fuzzy control algorithm. This paper proposes a fuzzy obstacle avoidance method with speed feedback based on the original advantages of the fuzzy algorithm, which improves the obstacle avoidance performance of space robot under continuous obstacles. At the same time, we integrated the improved fuzzy obstacle avoidance strategy into the behavior-based control technology, making the avoidance become an independent behavioral unit. Divide the path planning into a series of relatively independent behaviors such as fuzzy obstacle avoidance, cruise, trend target, and deadlock by the behavior-based method. According to the interaction information between the space robot and the environment, each behavior acquires the dominance of the robot through the competition mechanism, making the robot complete the specific behavior at a certain moment, and finally realize the path planning. Furthermore, to improve the overall fault tolerance of the space, robot we introduced an elegant downgrade strategy, so that the robot can successfully complete the established task in the case of control command deterioration or failure of important information, avoiding the overall performance deterioration effectively. Therefore, through the simulation experiment of the virtual environment platform, MobotSim concluded that the improved algorithm has high efficiency, high security, and the planned path is more in line with the actual situation, and the method proposed in this paper can make the space robot successfully reach the target position and optimize the spatial path, it also has good robustness and effectiveness.

Development of Dedicated Controller for HVAC

2012 ◽  
Vol 430-432 ◽  
pp. 1472-1476
Author(s):  
Jin Ming Yang ◽  
Yi Lin
Keyword(s):  
Fuzzy Control ◽  
Control Algorithm ◽  
Control Strategies ◽  
Control Software ◽  
Interface Circuits ◽  
Pid Algorithm ◽  
Hardware Interface ◽  
Hvac Control ◽  
Fuzzy Control Algorithm

This article describes the development of a dedicated controller for HVAC control, and introduces the hardware interface circuits about some main chip on controller. In addition, the article also explains composition and principle about control software applied to the controller, further more points out that the fuzzy control algorithm is more reasonable than the PID algorithm for most HVAC control and dedicated control strategies play an important role for HVAC control.

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