Modeling of Natural Ventilation Using a Hierarchical Fuzzy Control System for a New Energy-Saving Solar Greenhouse

2018 ◽  
Vol 34 (6) ◽  
pp. 953-962 ◽  
Author(s):  
Qingji Li ◽  
Dapeng Zhang ◽  
Jianwei Ji ◽  
Zhouping Sun ◽  
Yonggang Wang

Abstract. Natural ventilation as part of a greenhouse environment control system can save energy, reduce pollution, and cut the costs of production. Many studies have used the energy balance method to model greenhouse environments and calculate the rates of ventilation needed to control them. However, the efficacy of this method is influenced by many factors. There are often many parameters in the energy balance model, related to the greenhouse structure, crop growth, and climate. Thus, the effectiveness and applicability of greenhouse ventilation systems based on energy balance can be compromised. Here, we study a hierarchical fuzzy control method and use simple fuzzy logic controllers to control the coordination and opening angles of a new energy-saving solar greenhouse roof and sidewall ventilation. This design reduces the complexity of the fuzzy rule base and the fuzzy subsystem related to the physical model, therefore making it easy to design and build. The system uses the fuzzy tool in the Matlab environment, enabling a quick design, and the fuzzy inference engine fis.c file (Fuzzy Inference System) to load the design results into the fuzzy control system, thus making the modification and maintenance of the system easier. The experimental data showed that the new hierarchical fuzzy control reduced temperature fluctuations and maintained temperature closer to desired temperature than a non-fuzzy control method. Moreover, this method can also be easily used to control other equipment in the greenhouse. Keywords: Hierarchical fuzzy model, Natural ventilation, Matlab, Solar greenhouse.

2014 ◽  
Vol 1061-1062 ◽  
pp. 904-907
Author(s):  
Xiang Ping Chen

Considering the production status of red mud at present, an adaptive fuzzy control system, according to fuzzy control and genetic algorithm, has been focused on. With the control of flocculants, the system fuzzy control clarity of clear solution. Adaptive neural network fuzzy inference theory is adopted to establish the mathematical model of controlled object "black box", and MATLAB for simulation, showing that the control method has good accuracy and dynamic control quality. Satisfy the requirements of practice work.


2010 ◽  
Vol 159 ◽  
pp. 644-649
Author(s):  
Jing Hua Zhao ◽  
Wen Bo Zhang ◽  
He Hao

Based on the analysis of performance of vehicle and its suspension, half vehicle model of five DOF and road model were built and the dynamic equations of half vehicle were derived according to the parameters of a commercial vehicle. In addition, a novel fuzzy logic control system based on semi-active suspension was introduced to achieve the optimal vibration characteristic, with changing the adjustable dampers according to dynamic vertical body acceleration signal. The fuzzy control was designed based on non-reference model method that acceleration value was sent to the fuzzy controller directly. And then, simulation analysis of semi-active suspension with fuzzy control method were implemented on the B-class road surface. The results showed that the semi-active suspension control system introduced in this paper has better performance on vieicle vibration characteristic, compared to passive suspension.


2011 ◽  
Vol 71-78 ◽  
pp. 4184-4187
Author(s):  
Huan Zhang

As a new energy-saving and environmental protection building material, dry-mixed mortar has been promoting actively in China. The key techniques of control system for dry-mixed mortar production line were introduced in this paper, which was mainly based on PLC and smart weighing instrumentation. Firstly, the technology process and control demands were presented. Secondly, control system configuration, control strategy were proposed in detail. Finally, the key intelligent adjust algorithms were described as well. The practical operation verifies that the control system is highly reliable and stable, and it greatly enhances the level of automation and weighing accuracy of the raw material and meets the equipments requirements of energy-saving and green running.


2011 ◽  
Vol 328-330 ◽  
pp. 1904-1907
Author(s):  
Ming Xu ◽  
Bo Jin

A new energy-saving method with an energy regulation device (ERD) is presented. The ERD is composed of an accumulator, a proportional throttle valve and a safety valve. Due to the addition of the proportional throttle valve, the ERD becomes a flow-controllable element. It can adjust energy according to the system demand. The principle of energy regulation based close-loop variable-speed valve-controlled-motor is discussed in detail. And it can be conclude that the proposed close-loop scheme can gain a good response as the valve control system while the power is less obviously.


2000 ◽  
Vol 12 (6) ◽  
pp. 664-674
Author(s):  
Hidehiro Yamamoto ◽  
◽  
Takeshi Furuhashi

Fuzzy inference has a multigranular architecture consisting of symbols and continuous values, and has worked well to incorporate experts' know-how into fuzzy controls. Stability analysis of fuzzy control systems is one of the main topics of fuzzy control. A recently proposed stability analysis method on the symbolic level opened the door to the design of stable fuzzy controller using symbols. However the validity of the stability analysis in the symbolic system is not guaranteed in the continuous system. To guarantee this validity, a nonseparate condition has been introduced. If the fuzzy control system is asymptotically stable in the symbolic system and the system satisfies the nonseparate condition, the continuous system is also asymptotically stable. However this condition is too conservative. The new condition called a relaxed nonseparate condition has been proposed and the class of control systems with guaranteed discretization has been expanded. However the relaxed condition has been applicable only to controf systems having symmetric membership functions. This paper presents a new fuzzy inference method that makes the relaxed condition applicable to fuzzy control systems with asymmetric membership functions. Simulations are done to demonstrate the effectiveness of the new fuzzy inference method. The proof of the expansion of the relaxed nonseparate condition is also given.


2014 ◽  
Vol 568-570 ◽  
pp. 1131-1134
Author(s):  
Yan Jun Wang

By way of summarizes operation experience, using fuzzy control method to realize the decoupling control of coal mill cold air damper, hot air damper and coal feeder, by using cascade control of fuzzy control look up table and PI controller in DCS, it’s convenient to realized the automatic control of ball mill. Practice proves that this method is easy to achieve and good control effect could be achieved.


2012 ◽  
Vol 588-589 ◽  
pp. 1503-1506
Author(s):  
Fang Ding ◽  
Tao Ma

This Temperature control system of aircraft cabin is a complex system with nonlinear, time-varying, model inaccurate and work environment uncertain. According to the system control requirements, the fuzzy controller with the characteristic of fast response speed, good stability and strong resistance to interference is used in the study. The system error is adjusted constantly by using fuzzy control algorithm and simulation study is conducted in the software Matlab. The results are showed that control effect of control method used in this study is better than the traditional PID control method, and dynamic performance, steady state accuracy and robustness of system is effectively improved.


2016 ◽  
Vol 17 (7) ◽  
pp. 458-464
Author(s):  
M. V. Bobyr ◽  
◽  
S. A. Kulabuhov ◽  
A. S. Yakushev ◽  
◽  
...  

Author(s):  
Harendra Kumar

Defuzzification is a process that converts a fuzzy set or fuzzy number into a crisp value or number. Defuzzification is used in fuzzy modeling and in fuzzy control system to convert the fuzzy outputs from the systems to crisp values. This process is necessary because all fuzzy sets inferred by fuzzy inference in the fuzzy rules must be aggregated to produce one single number as the output of the fuzzy model.There are numerous techniques for defuzzifying a fuzzy set; some of the more popular techniques are included in fuzzy logic system. In the present chapter some recent defuzzification methods used in the literature are discussed with examples.


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