Speed Control of a DC Motor by Recurrent Fuzzy Logic Control Technique

被引:0
作者
Yasar, Banu Yilmaz [1 ]
Dursun, Mahir [2 ]
机构
[1] Gazi Univ Informat Inst, Dept Informat Syst, TR-06680 Ankara, Turkey
[2] Gazi Univ, Fac Technol, Dept Elect & Elect Engn, Tech Sch, TR-06500 Ankara, Turkey
来源
2021 8TH INTERNATIONAL CONFERENCE ON ELECTRICAL AND ELECTRONICS ENGINEERING (ICEEE 2021) | 2021年
关键词
DC motor; FLC; RFLC; ERFLC; MATLAB/SIMULINK; speed control; electrical vehicles;
D O I
10.1109/ICEEE52452.2021.9415935
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In the present paper, we deal with controlling of the angular speed of a direct current (DC) motor under some nonlinear loads constant, signal and step, performing with closed loop control system, FLC, Recurrent FLC (RFLC) and Enhanced Recurrent FLC (ERFLC) Techniques in MATLAB / SIMULINK FUNCTIONS via Gradient Descent Algorithm. We obtain transfer function satisfied by DC motor. Drawback of the literature Fuzzy Logic Control membership functions is not to regulate the voltage values directly in dynamic systems and so the performance of the microcontroller is too low. That is the reason why we use some MATLAB FUNCTIONS with recurrent algorithms. RFLC Technique appears to have an angular speed stabilizer feature on the DC motor after the first two seconds with much less oscillation under the entire load change, but FLC values are discrete. In the ERFLC Technique, the angular speed of a DC motor under nonlinear loads is achieved by reaching the reference angular speed value with much less oscillation when the total load changes completely and clearer results are obtained. Thus, RFLC and ERFLC Techniques can be used for precise positioning system, global trajectory planning system of an electrical autonomous vehicles. In decision making system of an electrical autonomous vehicles, RFLC and ERFLC can be used in the anti-lock braking system to downhill speed control in level three and as an electronic stability control in the level four with foggy airs such that the visibility is extremely low and provide safe driving on slippery and icy surfaces.
引用
收藏
页码:104 / 111
页数:8
相关论文
共 24 条
[1]  
ACIKGOZ H., 2018, INT J INTELLIGENT SY, V6, P197, DOI [10.18201/ijisae.2018644777, DOI 10.18201/IJISAE.2018644777]
[2]  
Ahmadi N., 2019, J SOFT COMPUT DECIS, V6, P15
[3]  
Aswathi ER, 2018, PROCEEDINGS OF THE 2018 SECOND INTERNATIONAL CONFERENCE ON INVENTIVE COMMUNICATION AND COMPUTATIONAL TECHNOLOGIES (ICICCT), P1661, DOI 10.1109/ICICCT.2018.8473242
[4]  
Cahyono Kurniawan, 2020, 2020 International Electronics Symposium (IES), P219, DOI 10.1109/IES50839.2020.9231882
[5]   Vision-based obstacle avoidance system with fuzzy logic for humanoid robots [J].
Chiang, Shu-Yin .
KNOWLEDGE ENGINEERING REVIEW, 2016, 32 :1-11
[6]  
Cviklovic V., 2016, Acta Technologica Agriculturae, V19, P19
[7]   An interval type-2 fuzzy logic controller design method for hydraulic actuators of a human-like robot by using improved drone squadron optimization [J].
Dong, Haozhen ;
Gao, Liang ;
Shen, Pi ;
Li, Xinyu ;
Lu, Yan ;
Dai, Wenyan .
INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS, 2019, 16 (06)
[8]  
Dursun Mahir, 2015, Journal of Automation and Control Engineering, V3, P336, DOI 10.12720/joace.3.4.336-342
[9]  
Ekpoudom I., 2017, Nigerian J. Technol, V36, P867
[10]   Hybrid control of a mechatronic system: Fuzzy logic and grey system modeling approach [J].
Erenturk, Koksal .
IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2007, 12 (06) :703-710