Compound intelligent control system combining fuzzy control with neural networks in a permanent magnetic synchronous motor

2005 ◽  
Author(s):  
Zhiyuan Zhang ◽  
Weili Li ◽  
Taifu Li
Keyword(s):  
Neural Networks ◽  
Control System ◽  
Fuzzy Control ◽  
Intelligent Control ◽  
Synchronous Motor ◽  
Intelligent Control System

scholarly journals Design and implementation of LED lighting intelligent control system for expressway tunnel entrance based on Internet of things and fuzzy control

2020 ◽  
Vol 16 (5) ◽  
pp. 155014772092574
Author(s):  
Ying Lu ◽  
Jin Wang ◽  
Xiaojun Bai ◽  
Hehan Wang
Keyword(s):  
Control System ◽  
Internet Of Things ◽  
Fuzzy Control ◽  
Traffic Flow ◽  
Intelligent Control ◽  
Flow Speed ◽  
Led Lighting ◽  
Intelligent Control System ◽  
Entrance Section ◽  
Tunnel Entrance

Due to the special characteristics of highway tunnels and vehicles, the interior of the tunnel is required to provide appropriate lighting to ensure the safety of driving vehicles, especially at the entrance section of the tunnel. At present, most of the tunnel entrance lighting control system only considers one single factor, the brightness outside the tunnel. However, in practice, the required lighting brightness in the tunnel is also related to traffic flow, speed, and other factors. Comprehensively utilizing these factors to improve the control strategy is urgently needed. To deal with this problem, this article has designed a multi-source information acquisition system for tunnel lighting based on the Internet of things technology, which combined with fuzzy control theory in order to develop an intelligent control system for LED lighting at the entrance section of the tunnel. The designed system was implemented and long-term tested in a real highway tunnel. The experimental results have shown that the system designed in this article can automatically control the brightness of the lighting inside the tunnel according to the real-time measurements of the brightness outside the tunnel, traffic flow, speed, and so on. Furthermore, the utilizations of the system can minimize the human and power consumption of tunnel lighting while ensuring the safety of tunnel traffic.

scholarly journals THE INTELLIGENT ROBOT MITSUBISHI RV-2JA CONTROL SYSTEM

2020 ◽  
Author(s):  
V.F. Bonilla ◽  
◽  
A.V. Litvin ◽  
M.H. Moya ◽  
G.K Moskera ◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Control System ◽  
Intelligent Control ◽  
Robot Control ◽  
Intelligent Robot ◽  
Intelligent Control System ◽  
And Control ◽  
Electromyographic Signals ◽  
Semg Signals

The Mitsubishi RV-2JA intelligent robot control system (ISMS) was synthesized using surface electromyographic signals (pEMG). The sEMG signals were recording using the Myo bracelet and transmitted to the intelligent control system via the Bluetooth interface. The IRCS was synthesized in Simulink environment of the Matlab platform. IRCS performs the processing and analysis of sEMIG signals to identify, verify and control the robot using an artificial neural networks.

scholarly journals Intelligent Technologies and Robotic Machines for Garden Crops Cultivation

2021 ◽  
Vol 15 (4) ◽  
pp. 35-41
Author(s):  
I. G. Smirnov ◽  
D. O. Khort ◽  
A. I. Kutyrev
Keyword(s):  
Neural Networks ◽  
Control System ◽  
Intelligent Control ◽  
Industrial Robots ◽  
Fixation Time ◽  
Software Environment ◽  
Technical Standards ◽  
Real Time Processing ◽  
Software Complex ◽  
Intelligent Control System

The existing models of industrial robots cannot perform technological processes of apple harvesting. It is noted that there is a need for developing special actuators, grippers and new control algorithms for harvesting horticulture products. (Research purpose) The research aimed to develop an intelligent control system for horticulture industrial technologies and robotic techniques for yield monitoring and fruit harvesting. (Materials and methods) The research methodology was based on such modern methods as computer modeling and programming. In particular, the following methods were applied: systems analysis, artificial neural networks theory, pattern recognition, digital signal processing. The development of software, hardware and software was carried out in accordance with the requirements of GOST technical standards. The following programming languages were used: (C / C ++)-based  OpenCV library, Spyder Python Development Environment, PyTorch and Flask frameworks, and JavaScript. Image marking for training neural networks was carried out via VGG ImageAnnotator and in Labelbox. The design process was based on the finite element method, CAD SolidWorks software environment. (Results and discussion) An intelligent management system for horticulture industrial technologies has been created based the on the «Agrointellect VIM» hardware and software complex. The concept of the system is shown to be implemented via computer and communication technology, robotic machines, the software for collecting, organizing, analyzing and storing data. The gripper proves to fix an apple gently and holds it securely. Depending on the size, the fruit fixation time is 1.5-2.0 seconds, the fruit maximum size is 85 per 80 millimeters , and its maximum weight is 500 grams. (Conclusions) The developed intelligent control system for industrial technologies based on «Agrointellect VIM» hardware and software complex ensures the efficient real-time processing of information necessary for the design of intelligent agricultural technologies using robotic machines and artificial intelligence systems.

A framework of fuzzy control-based intelligent control system for greenhouse

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Yi-Han Xu ◽  
Wen-Li Wu ◽  
Yong Xu ◽  
Mau-Luen Tham ◽  
Nordin Ramli
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Intelligent Control ◽  
Intelligent Control System
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