Start Control of Ultrasonic Motor Based on Neural Network

2011 ◽  
Vol 383-390 ◽  
pp. 1623-1628
Author(s):  
Hui Min Zhang ◽  
Hai Yan Wang ◽  
Jing Zhuo Shi ◽  
Xun Liu
Keyword(s):  
Neural Network ◽  
Traveling Wave ◽  
High Speed ◽  
Control Algorithm ◽  
Ultrasonic Motor ◽  
Tuning Parameters ◽  
Speed Controller ◽  
Self Tuning ◽  
On Line

It is very hard for the traveling wave ultrasonic motor to start directly with high speed, because of their special running mechanism and the unique features. To solve this problem and realize the uitrasonic motor’s high-speed start control, speed controller with on-line self-tuning parameters is designed. Neural network is used to realize the online adjustment of controller’s parameters, to agree with the different starting request of different speed references, and make best use of motor’s ability. The experiments indicated that the motor start fast and accurately, the control algorithm is effective and reliable.

scholarly journals Neural Networks for Self-tuning Control Systems

10.14311/514 ◽  
2004 ◽  
Vol 44 (1) ◽  
Author(s):  
A. Noriega Ponce ◽  
A. Aguado Behar ◽  
A. Ordaz Hernández ◽  
V. Rauch Sitar
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Control Systems ◽  
Control Algorithm ◽  
Set Point ◽  
Tuning Mechanism ◽  
Self Tuning ◽  
The Moment ◽  
Weighting Coefficients ◽  
Previous Training

In this paper, we presented a self-tuning control algorithm based on a three layers perceptron type neural network. The proposed algorithm is advantageous in the sense that practically a previous training of the net is not required and some changes in the set-point are generally enough to adjust the learning coefficient. Optionally, it is possible to introduce a self-tuning mechanism of the learning coefficient although by the moment it is not possible to give final conclusions about this possibility. The proposed algorithm has the special feature that the regulation error instead of the net output error is retropropagated for the weighting coefficients modifications. 

scholarly journals A NEAT Based Two Stage Neural Network Approach to Generate a Control Algorithm for a Pultrusion System

AI ◽  
2021 ◽  
Vol 2 (3) ◽  
pp. 355-365
Author(s):  
Christian Pommer ◽  
Michael Sinapius ◽  
Marco Brysch ◽  
Naser Al Al Natsheh
Keyword(s):  
Neural Network ◽  
Control Systems ◽  
High Speed ◽  
Control Algorithm ◽  
Time Frame ◽  
Physical Processes ◽  
Neural Network Approach ◽  
Alternative Approach ◽  
Reasonable Time Frame ◽  
Speed Training

Controlling complex systems by traditional control systems can sometimes lead to sub-optimal results since mathematical models do often not completely describe physical processes. An alternative approach is the use of a neural network based control algorithm. Neural Networks can approximate any function and as such are able to control even the most complex system. One challenge of this approach is the necessity of a high speed training loop to facilitate enough training rounds in a reasonable time frame to generate a viable control network. This paper overcomes this problem by employing a second neural network to approximate the output of a relatively slow 3D-FE-Pultrusion-Model. This approximation is by orders of magnitude faster than the original model with only minor deviations from the original models behaviour. This new model is then employed in a training loop to successfully train a NEAT based genetic control algorithm.

scholarly journals DRNN Robust DTC for Induction Motor Drive Systems Using FSTPI

2021 ◽  
Vol 54 (4) ◽  
pp. 539-547
Author(s):  
Lucky Dube ◽  
Ehab H.E. Bayoumi
Keyword(s):  
High Speed ◽  
Direct Torque Control ◽  
Torque Control ◽  
Speed Controller ◽  
Three Phase ◽  
Motor Parameter ◽  
Self Tuning ◽  
Drive Systems ◽  
Stator Resistance ◽  
Three Phase Inverter

In this paper, a self-tuning PI speed controller based on diagonal recurrent neural network is (DRNN) investigated and simulated to increase the robustness of the direct torque control (DTC) scheme for three-phase low-power IM drive system using a Four Switch Three-Phase Inverter (FSTPI). The drive is subjected to different system inputs and disturbances, step changes in speed under different load conditions, abrupt loading at high speed and speed reversal. Furthermore, the robustness of the controller is evaluated by varying motor parameter, stator resistance and moment of inertia. A comparison of classical and self-tuning PI speed controllers was presented to determine the effectiveness of the proposed controller. It is concluded based on simulation results using Matlab/Simulink. that the self-tuning PI speed controller provides the best performance by reacting rapidly and adaptively.

scholarly journals SELF-TUNING FUZZY SPEED CONTROLLER OF TRAVELLING WAVE ULTRASONIC MOTOR

2014 ◽  
Vol 7 (1) ◽  
pp. 301-320 ◽  
Author(s):  
Jingzhuo Shi ◽  
Juanping Zhao ◽  
Zhe Cao ◽  
Yunpeng Liang ◽  
Lan Yuan ◽  
...  
Keyword(s):  
Travelling Wave ◽  
Ultrasonic Motor ◽  
Speed Controller ◽  
Self Tuning
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