A Neural Network Based Control System for a Mobile Robot Employing Link Mechanism

Author(s):  
M. Sato ◽  
K. Ishii
2012 ◽  
Vol 522 ◽  
pp. 618-622
Author(s):  
Ying Xiong ◽  
Shi De Xiao ◽  
Shuang Jiang Lei ◽  
Feng Zha

An intelligent tracking control system based on the micro-control unit (MCU) has been developed to control the motors by sensing the change of black guide lines. After the training of the BP Neural Network, the MCU is able to make decisions quickly and accurately for various situations during robot moving. Using MCU technology to control the motors, the system is compatible for both manual and automatic control. The experiment shows that the mobile robot could follow the change of black guide lines accurately and quickly, and stillness and out-of-orbit were effectively inhibited during moving. The proposed tracking control system based on the BP Neural Network has been verified to have high reliability.


2019 ◽  
pp. 41-48
Author(s):  
Yan Guojun ◽  
Oleksiy Kozlov ◽  
Oleksandr Gerasin ◽  
Galyna Kondratenko

The article renders the special features of the design of a tracked mobile robot (MR) for moving over inclined ferromagnetic surfaces while performing specified technological operations. There is conducted a synthesis of the functional structure and selective technological parameters (such as control coordinates) of the computerized monitoring and control system (CMCS) intended for use with this MR. Application of the CMCS with the proposed functional structure allows substantially increasing the accuracy of the MR monitoring and control, which in turn provides for a considerable enhancement in the quality and economic efficiency of the operations on processing of large ferromagnetic surfaces.


2010 ◽  
Vol 7 ◽  
pp. 109-117
Author(s):  
O.V. Darintsev ◽  
A.B. Migranov ◽  
B.S. Yudintsev

The article deals with the development of a high-speed sensor system for a mobile robot, used in conjunction with an intelligent method of planning trajectories in conditions of high dynamism of the working space.


2011 ◽  
Vol 110-116 ◽  
pp. 4076-4084
Author(s):  
Hai Cun Du

In this paper, we determine the fuzzy control strategy of inverter air conditioner, the fuzzy control model structure, the neural network and fuzzy control technology, structural design of the fuzzy neural network controller as well as the neural network predictor FNNC NNP. Simulation results show that the fuzzy neural network controller can control the accuracy greatly improved the compressor, and the control system has strong adaptability to achieve a truly intelligent; model of the controller design and implementation of technology are mainly from the practical point of view, which is practical and feasible.


2021 ◽  
pp. 1-15
Author(s):  
Qinyu Mei ◽  
Ming Li

Aiming at the construction of the decision-making system for sports-assisted teaching and training, this article first gives a deep convolutional neural network model for sports-assisted teaching and training decision-making. Subsequently, In order to meet the needs of athletes to assist in physical exercise, a squat training robot is built using a self-developed modular flexible cable drive unit, and its control system is designed to assist athletes in squatting training in sports. First, the human squat training mechanism is analyzed, and the overall structure of the robot is determined; second, the robot force servo control strategy is designed, including the flexible cable traction force planning link, the lateral force compensation link and the establishment of a single flexible cable passive force controller; In order to verify the effect of robot training, a single flexible cable force control experiment and a man-machine squat training experiment were carried out. In the single flexible cable force control experiment, the suppression effect of excess force reached more than 50%. In the squat experiment under 200 N, the standard deviation of the system loading force is 7.52 N, and the dynamic accuracy is above 90.2%. Experimental results show that the robot has a reasonable configuration, small footprint, stable control system, high loading accuracy, and can assist in squat training in physical education.


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