Pumping System Controlled by Neuro-fuzzy

被引:0
|
作者
Smail, Mansouri [1 ]
Omar, Ouled Ali [2 ]
机构
[1] Univ Ahmed Draia Adrar, Sci & Technol Fac, Lab EESI, Adrar, Algeria
[2] Univ Ahmed Draia Adrar, Sci & Technol Fac, Lab LDDI, Adrar, Algeria
关键词
DFIM; fuzzy control; neuro-fuzzy control; speed;
D O I
10.3934/energy.2019.5.634
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The irrigation system in Foggara is adopted by peasants in the Algerian south. Over the years, the water level in the vertebrates has decreased, which has caused the migration of many peasants to their traditional agricultural lands. The studied system aims to strengthen the Foggara with deep wells that rely on large pumps, which are rotated by electric machines of high capacity. To ensure the maintenance of the water level, we control the speed of the DFIM machine and thus control the level of water flow. The controlled type of control is the control of the neuro-fuzzy, because it has many positive properties, for example, not associated with changes related to the electrical properties of the machine, such as resistance, self, etc.
引用
收藏
页码:634 / 645
页数:12
相关论文
共 50 条
  • [21] Development of neuro-fuzzy system for image mining
    Maghooli, K
    Moghadam, AME
    FUZZY LOGIC AND APPLICATIONS, 2006, 3849 : 32 - 39
  • [22] Face Recognition Based on Neuro-Fuzzy System
    Makhsoos, Nina Taheri
    Ebrahimpour, Reza
    Hajiany, Alireza
    INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND NETWORK SECURITY, 2009, 9 (04): : 319 - 326
  • [23] Deep neuro-fuzzy system for violence detection
    Mishra, Sidharth
    Jain, Vishal
    Saraf, Yash Ajay
    Kandasamy, Ilanthenral
    Vasantha, W. B.
    NEUROCOMPUTING, 2025, 619
  • [24] A neuro-fuzzy system for patch load prediction
    Fonseca, E. T.
    Vellasco, P. C. G. da S.
    Vellasco, M. M. B. R.
    de Andrade, S. A. L.
    Proceedings of The Seventh International Conference on the Application of Artificial Intelligence to Civil and Structural Engineering, 2003, : 113 - 114
  • [25] Neuro-Fuzzy Modelling of Wastewater Treatment System
    Gaya, Muhammad Sani
    Wahab, Norhaliza Abdul
    Sam, Yahya Md
    Razali, Mashitah Che
    Samsudin, S. I.
    2012 IEEE INTERNATIONAL CONFERENCE ON CONTROL SYSTEM, COMPUTING AND ENGINEERING (ICCSCE 2012), 2012, : 250 - 253
  • [26] Neuro-fuzzy control for pneumatic servo system
    Shibata, S
    Jindai, M
    Shimizu, A
    IECON 2000: 26TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY, VOLS 1-4: 21ST CENTURY TECHNOLOGIES AND INDUSTRIAL OPPORTUNITIES, 2000, : 1761 - 1766
  • [27] EVOLVING NEURO-FUZZY SYSTEM COMBINED LEARNING
    Deineko, A. A.
    Pliss, I. P.
    Ye, Bodyanskiy
    RADIO ELECTRONICS COMPUTER SCIENCE CONTROL, 2012, 1 : 86 - 92
  • [28] A self-learning neuro-fuzzy system
    DeClaris, N
    Su, MC
    HYBRID SYSTEMS II, 1995, 999 : 106 - 127
  • [29] Negotiation strategy based on neuro-fuzzy system
    Peng, Zhi-Ping
    Li, Shao-Ping
    Xitong Fangzhen Xuebao / Journal of System Simulation, 2008, 20 (03): : 623 - 626
  • [30] Memetic Neuro-Fuzzy System with Differential Optimisation
    Siminski, Krzysztof
    BEYOND DATABASES, ARCHITECTURES AND STRUCTURES, BDAS 2016, 2016, 613 : 135 - 145