Design of Greenhouse Wireless Sensor Network Control System Based on Fuzzy Neural Network

2011 ◽  
Vol 464 ◽  
pp. 318-321
Author(s):  
Rong Biao Zhang ◽  
Li Hong Wang ◽  
Xian Lin Huang ◽  
Jing Jing Guo
Keyword(s):  
Neural Network ◽  
Control System ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Fuzzy Neural Network ◽  
Network Control ◽  
Environmental Data ◽  
Wireless Sensor ◽  
Wireless Sensor Node ◽  
Fuzzy Neural

This paper proposed a greenhouse control system utilizing wireless sensor network (WSN) to overcome the wiring difficulties and poor mobility in the application of traditional cable-used control systems. Each wireless sensor node in the WSN collects the environmental data of temperature, humidity and CO2 concentration, and transmits the data to the control center via the sink nodes. A fuzzy neural network with three inputs and six outputs was designed to improve the control accuracy. By analyzing the relationship between the mentioned environmental factors above and the actuators of the system, a fuzzy rule was made and combined with the neural network. The simulation results showed that the proposed method could respond in a short time with high accuracy, and had small overshoot as well as good stability.

scholarly journals A New Method for Reliability Evaluation of Wireless Sensor Networks Based on Fuzzy Neural Network

2018 ◽  
Vol 14 (10) ◽  
pp. 180
Author(s):  
Jianjun Xu
Keyword(s):  
Neural Network ◽  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Fuzzy Neural Network ◽  
Evaluation Model ◽  
Reliability Evaluation ◽  
Wireless Sensor ◽  
Performance Indexes ◽  
Fuzzy Neural

<span style="font-family: 'Times New Roman',serif; font-size: 10pt; mso-fareast-font-family: 'Times New Roman'; mso-fareast-language: DE; mso-ansi-language: EN-US; mso-bidi-language: AR-SA;">In this paper, a reliability evaluation model based on fuzzy neural network is proposed to evaluate the reliability of wireless sensor networks without a unified standard. Firstly, the reliability is analyzed from the point of view of topology structure, protocol stack structure and reliability mechanism of wireless sensor network, and the performance indexes that affect the reliability are extracted. Secondly, some performance indexes are screened out, and the standard value matrix of reliability evaluation for index fuzzy quantization is established. The sample data is generated by interpolation, and the reliability evaluation model based on fuzzy neural network is established. The neural network model takes the selected index values as input, and outputs are the reliability of the wireless sensor network. The simulation results show that the evaluation model is basically consistent with the actual situation, and it can evaluate the wireless sensor network from the system level.</span>

Adaptive Fuzzy Neural Network Control System in Cylindrical Grinding Process

2010 ◽  
Vol 426-427 ◽  
pp. 220-224
Author(s):  
X.M. Li ◽  
Ning Ding
Keyword(s):  
Neural Network ◽  
Control System ◽  
Fuzzy Neural Network ◽  
Network Control ◽  
Grinding Process ◽  
Neural Network Control ◽  
Network Control System ◽  
Cylindrical Grinding ◽  
Adaptive Fuzzy Neural Network ◽  
Fuzzy Neural

An adaptive fuzzy neural network control system in cylindrical grinding process was proposed. In this system, the initial cylindrical grinding parameters were decided by the expert system based on fuzzy neural network. Multi-feed and setting overshoot optimization methods were also adopted during the grinding process, and a human machine cooperation system (composed of human and two fuzzy – neural networks) could revise the process parameters in real-time. The experiment of the cylindrical grinding was implemented. The results showed that this control system was valid, and could greatly improve the cylindrical grinding quality and machining efficiency.

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