Simulation and Application of Fuzzy Control System with Integrator

2011 ◽  
Vol 418-420 ◽  
pp. 1825-1828
Author(s):  
Ping Li ◽  
Chang Feng Yan ◽  
Ling Ke Zeng ◽  
Xiao Su Cheng
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Control Systems ◽  
Practical Experience ◽  
System Stability ◽  
Static Error ◽  
Fuzzy Control System ◽  
Simulation Results ◽  
The Stability

This article simulated fuzzy control system by using MATLAB and compared the normal fuzzy control system with the fuzzy control system which has an integrator. Further more, the influence of quantize factors, proportional factors and integral constants on system was studied. The simulation results show that static error always exists in normal fuzzy control systems and proportional factors influence the stability of the system greatly. Put an integrator into a fuzzy control system, and static error can be eliminated and the system stability can be improved. The conclusion of simulation and practical experience, use fuzzy control system with integrator in reality. It can get good results.

Creation of Fuzzy Control Table with Data Mining

2013 ◽  
Vol 760-762 ◽  
pp. 1080-1083
Author(s):  
Jun Gao
Keyword(s):  
Data Mining ◽  
Control System ◽  
Fuzzy Control ◽  
Control Systems ◽  
Association Rule ◽  
New Method ◽  
Data Mining Techniques ◽  
Fuzzy Control System

A good fuzzy control table is the key to a fuzzy control system, and the systems performance mainly depends on the quality of the table. Based on analyzing fully the principles of a typical fuzzy control systems and the procedures of building a fuzzy control table, this paper presents a new method of applying the boolean association rule data mining techniques to mining of fuzzy control table directly from the database of manual operating records.

scholarly journals The research of the pulse oxygen supply based on the fuzzy control technology

2018 ◽  
Vol 189 ◽  
pp. 06012
Author(s):  
Faling Hu ◽  
Tongfeng Niu ◽  
Jun Yao ◽  
Bingyan Cui ◽  
Haoxing Xu ◽  
...  
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Open Loop ◽  
Open Loop Control ◽  
Loop Control ◽  
Fuzzy Control System ◽  
Loop Control System ◽  
Working Principle ◽  
The Stability ◽  
Close Loop Control

According to the working principle of pulse oxygen supplies, we analyze how to realize the control of the oxygen flow by double different valves. a two-dimensional fuzzy control system is proposed to solve the unstable problem, which is brought by the shortcomings of the open-loop control system. We add a new parameter, the rate of the differential pressure signal changes, which contributes to a close –loop control system and increases the stability of the system. The experiments and the data show that the fuzzy control system make the process of breathing much more comfortable and solve the hysteresis and overshoot caused by the open-loop control system. The product reliability has been greatly improved.

Stability Analysis of Nonlinear Dynamic Systems by Nonlinear Takagi–Sugeno–Kang Fuzzy Systems

2013 ◽  
Vol 136 (2) ◽  
Author(s):  
Zahra Namadchian ◽  
Assef Zare ◽  
Ali Namadchian
Keyword(s):  
Control System ◽  
Stability Analysis ◽  
Fuzzy Control ◽  
Limit Cycle ◽  
Phase Margin ◽  
Fuzzy Control System ◽  
Gain Margin ◽  
The Stability ◽  
Takagi Sugeno ◽  
System 1

This paper proposes a systematic procedure to address the limit cycle prediction of a Nonlinear Takagi–Sugeno–Kang (NTSK) fuzzy control system with adjustable parameters. NTSK fuzzy can be linearized by describing function method. The stability of the equivalent linearized system is then analyzed using the stability equations and the parameter plane method. After that the gain–phase margin (PM) tester has been added, then gain margin (GM) and phase margin for limit cycle are analyzed. Using NTSK fuzzy control system can help to have fewer rules. In order to analyze the stability with the same technique of stability analysis, the results of NTSK fuzzy control system will be compared with Dynamic fuzzy control system [1]. Computer simulations show differences between both systems.

The Stability Conditions Evaluation of Network Control System Based on Double Time Delay Discrete Model

2013 ◽  
Vol 846-847 ◽  
pp. 112-115
Author(s):  
Ling Ding ◽  
Ping Fan ◽  
Bin Wen
Keyword(s):  
Control System ◽  
Time Delay ◽  
Control Systems ◽  
Discrete Model ◽  
Network Control ◽  
System Stability ◽  
Stability Conditions ◽  
Network Control System ◽  
Network Control Systems ◽  
The Stability

The current study of network control stability system has become a very hot topic, the stability conditions of network control systems have also carried out the relevant research on double delay discrete model, its main target to the current actual situation, which carries out the related stability for network control systems with state time-delay. This paper uses the relevant stability theory, the sufficient condition of network control system stability are described under the time-delay discrete model, on the basis of relevant transformation, completing the evaluation for the network control system stability condition of double delay discrete model. Finally, through the relevant data, to carry on its effectiveness validated. The method has certain reference significance for the stability study of similar system, and provides a theoretical reference for the research on this problem.

Computer Simulations for Design and Optimization of a Fuzzy Control System

1994 ◽  
Author(s):  
Dean B. Edwards ◽  
John R. Canning ◽  
Anthony de Sam Lazaro
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Control Systems ◽  
Computer Simulations ◽  
Fuzzy Systems ◽  
Linear Control ◽  
Control Problems ◽  
Trial And Error ◽  
Fuzzy Control System ◽  
Design And Optimization

Abstract The use of fuzzy logic in control systems is becoming increasingly popular as a method of handling non-linear control problems. The design of fuzzy systems is generally undertaken using intuition and a trial-and-error approach for tuning. A system so developed may be less than optimum as no accepted evaluation norms are available. In this paper a generic method to design and to optimize a fuzzy control system is developed. The results of computer simulations of a system constructed using this technique are submitted and discussed. The experimental verification of the method is presented.

Study on Range of the Sampling Period of the Electro-Hydraulic Position Sampling Control System Based on PLC

2010 ◽  
Vol 152-153 ◽  
pp. 58-62
Author(s):  
He Ying Bian ◽  
Yan Hui Wang
Keyword(s):  
Control System ◽  
Closed Loop ◽  
Simulation Analysis ◽  
Sampling Period ◽  
System Stability ◽  
Practical Significance ◽  
Theory Of Sampling ◽  
Actual Operation ◽  
Simulation Results ◽  
The Stability

The paper built electro-hydraulic position closed-loop sampling control system based on PLC, established mathematical model of this system by applying theory of sampling control and determines the range of the sampling period T under the stability of the system according to system stability theory. Then carried out simulation analysis and experimental verification in the range of T, provided with the method determined the range of sampling period. The results showed that simulation results of this model were consistent with the actual operation of the system , the method and sampling period be chosen have some practical significance.

The Temperature and Humidity Based on the Embedded Implementation of Fuzzy Control System

2011 ◽  
Vol 58-60 ◽  
pp. 749-754
Author(s):  
Jun Zhang
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Control Systems ◽  
Humidity Control ◽  
Fuzzy Control System ◽  
Temperature And Humidity ◽  
Cut Set ◽  
Transition Rules ◽  
And Control ◽  
Embedded Implementation

For the characteristics and needs of temperature and humidity control in current industrial environment, the paper proposes a fuzzy-based embedded temperature and humidity control system，which enables consumers monitor and control temperature and humidity parameters through the PDA when moving. The article first introduces the hardware structure of the temperature and humidity fuzzy control system, then based on the theory of fuzzy set and the fuzzy number operations of l - cut set, focusing on the transition rules of fuzzy controlling fuzzy conditions of the temperature and humidity control systems, and finally introduce the key technologies of embedded software system of the PDA,. The experimental results show that the system is very practical and flexible.

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