scholarly journals Development and Experimental Analysis of a Fuzzy Grey Control System on Rapeseed Cleaning Loss

Electronics ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1764
Author(s):  
Xiaoyu Chai ◽  
Lizhang Xu ◽  
Yang Li ◽  
Jie Qiu ◽  
Yaoming Li ◽  
...  
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Field Tests ◽  
Grey Prediction ◽  
Control Scheme ◽  
Cleaning Device ◽  
Important Means ◽  
Prediction Control ◽  
Microcontroller Unit ◽  
Control Principle

One of the most important means of improving the mechanization of rapeseed harvests and increasing farmers’ income is to reduce the cleaning loss of rapeseed. In this study, a fuzzy grey control system was developed using an assembled cleaning loss sensor. Based on experimental data, the relationship between the cleaning loss and the opening of the louver sieve in the cleaning device was obtained. The fuzzy control scheme was established by combining grey prediction and the fuzzy control principle. Secondly, a microcontroller unit (MCU) was used as the controller, and the opening of the louver sieve was automatically regulated by detecting the signal of the cleaning loss. Finally, the performance and robustness of the control system was evaluated in field tests. Different experiments were conducted under different speed conditions to reflect the variable throughput. Results showed that using the grey prediction control system can realize the adjustment of the louver sieve opening in real time. The cleaning loss could be maintained within the ideal setpoint interval, compared with the operation with the control system switched off. These findings indicate that the application of the grey fuzzy control system reduces cleaning loss, and the nonlinear, time-variable and time delay problems in cleaning devices can be solved effectively.

Temperature Control System Based on Electronic Boiler

2013 ◽  
Vol 325-326 ◽  
pp. 1197-1201
Author(s):  
Guo Sheng Xu
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Temperature Control ◽  
Fuzzy Controller ◽  
System Simulation ◽  
Temperature Control System ◽  
Control Effect ◽  
Simulation Research ◽  
Control Regulation ◽  
Control Scheme

Research has been done aimed at the boiler's temperature control system, and available control scheme is put forward. Combining with the output response of control system, simulation research and the control regulation of fuzzy controller are done to analyse, after experiments for many times repeatedly, fuzzy control regulation is ensured. The simulation result indicates that control effect is ideal, which means this scheme is identified as ideal temperature control system scheme.

Fuzzy Control of a Novel Type of Translational Meshing Motors

2010 ◽  
Vol 121-122 ◽  
pp. 1038-1043
Author(s):  
Wei Wang ◽  
Xin Jian Shan ◽  
Shi Min Wei
Keyword(s):  
Neural Network ◽  
Control System ◽  
Fuzzy Control ◽  
Fuzzy Controller ◽  
Torque Control ◽  
Training Procedure ◽  
Test Results ◽  
Model Reference Control ◽  
The Neural Network ◽  
Control Scheme

Owing to the nonlinear characteristic of a novel type of translational meshing motor with model uncertainties, a model reference control system which consists of a neural network and a fuzzy controller is used. The torque model is identified based on BP neural network, and then Fuzzy controller works as the controller. The description of the control system and training procedure of the neural network are given. The test results obtained for a torque control scheme suitable for the control of the motor are also presented to verify the effectiveness of the proposed nonlinear control scheme. It has been found that the fuzzy control system is able to work reliably.

Fuzzy Control Strategy of the Mixed Magnetic Levitation Bearing Rotor System

2012 ◽  
Vol 184-185 ◽  
pp. 1566-1569
Author(s):  
Xiao Bin Zhou ◽  
Li Zeng ◽  
Zheng Jie Xu ◽  
Dao Tian Hu ◽  
Yan Neng Yang
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Control Strategy ◽  
Magnetic Levitation ◽  
Magnetic Suspension ◽  
Displacement Sensor ◽  
Fuzzy Pid ◽  
Fuzzy Pid Controller ◽  
Fuzzy Control Strategy ◽  
Control Principle

This paper proposes a Fuzzy Control strategy of magnetic levitation bearing rotor according to the mixed magnetic levitation bearing. Combined with electromagnetic winding working principle, this paper uses the self-sensing displacement self-diagnosing system instead of the special displacement sensor, makes a no sensor self-diagnosing magnetic suspension control system, controls the system by the fuzzy PID (proportional, integral and differential) controller, and builds a mathematical model of the control system. Analyzing the fuzzy rules and fuzzy control principle of the fuzzy PID controller setting parameters, this paper has a fuzzy simulation for the system.

scholarly journals Multivariable Fuzzy Control Based Mobile Robot Odor Source Localization via Semitensor Product

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Ping Jiang ◽  
Yuzhen Wang ◽  
Aidong Ge
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Mobile Robot ◽  
Source Localization ◽  
Odor Source ◽  
Algebraic Equations ◽  
Fuzzy Control System ◽  
Control Rules ◽  
Control Scheme ◽  
Set Up

In order to take full advantage of the multisensor information, a MIMO fuzzy control system based on semitensor product (STP) is set up for mobile robot odor source localization (OSL). Multisensor information, such as vision, olfaction, laser, wind speed, and direction, is the input of the fuzzy control system and the relative searching strategies, such as random searching (RS), nearest distance-based vision searching (NDVS), and odor source declaration (OSD), are the outputs. Fuzzy control rules with algebraic equations are given according to the multisensor information via STP. Any output can be updated in the proposed fuzzy control system and has no influence on the other searching strategies. The proposed MIMO fuzzy control scheme based on STP can reach the theoretical system of the mobile robot OSL. Experimental results show the efficiency of the proposed method.

Application of Grey Model in Intelligent-Control of Micro-Hole Abrasive Flow Machining

2014 ◽  
Vol 1039 ◽  
pp. 403-408
Author(s):  
Shu Zhen Yang ◽  
Wei Jin ◽  
Yu Jie Bai
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Intelligent Control ◽  
Machining Accuracy ◽  
Grey Prediction ◽  
Abrasive Flow Machining ◽  
Fuzzy Control System ◽  
Micro Hole ◽  
Processing Requirement ◽  
Processing Flow

In this paper, a control system based on the prediction of processing flow in Abrasive flow machining is designed. In this system,flow is predicted by an improved GM(1,1) model in conformation of background value. Combined with fuzzy control system, it can adapt the pressure to meet the processing requirement automatically. Experiments proved that the improved GM(1,1) model can predict the processing flow accuratly, and the fuzzy control system based on grey prediction can improve the machining accuracy of micro-hole AFM effectively.

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