An adaptive inverse control method based on SVM–fuzzy rules acquisition system for pulsed GTAW process

2009 ◽  
Vol 44 (7-8) ◽  
pp. 686-694 ◽  
Author(s):  
Xixia Huang ◽  
Wei Gu ◽  
Fanhuai Shi ◽  
Shanben Chen
Keyword(s):  
Control Method ◽  
Fuzzy Rules ◽  
Acquisition System ◽  
Adaptive Inverse Control ◽  
Inverse Control ◽  
Pulsed Gtaw ◽  
Gtaw Process ◽  
Rules Acquisition

SVM-based fuzzy rules acquisition system for pulsed GTAW process

2009 ◽  
Vol 22 (8) ◽  
pp. 1245-1255 ◽  
Author(s):  
Xixia Huang ◽  
Fanhuai Shi ◽  
Wei Gu ◽  
Shanben Chen
Keyword(s):  
Fuzzy Rules ◽  
Acquisition System ◽  
Pulsed Gtaw ◽  
Gtaw Process ◽  
Rules Acquisition

scholarly journals Adaptive Inverse Control Based on Kriging Algorithm and Lyapunov Theory of Crawler Electromechanical System

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-12
Author(s):  
Guanyu Zhang ◽  
Yitian Wang ◽  
Yiyao Fan ◽  
Chen Chen
Keyword(s):  
Electromechanical Coupling ◽  
Control Method ◽  
Coupling Model ◽  
Virtual Prototype ◽  
Lyapunov Theory ◽  
Electromechanical System ◽  
Prototype Model ◽  
Control Effect ◽  
Adaptive Inverse Control ◽  
Inverse Control

The electromechanical system of a crawler is a multi-input, multioutput strongly coupled nonlinear system. In this study, an adaptive inverse control method based on kriging algorithm and Lyapunov theory is proposed to improve control accuracy during adaptive driving. The electromechanical coupling model of the electromechanical system is established on the basis of the dynamic analysis of the crawler. In accordance with the kriging algorithm, the inverse model of the electromechanical system of the crawler is established by offline data. The adaptive travel control law of the crawler is obtained on the basis of Lyapunov theory. Combined with the kriging algorithm, the adaptive driving reverse control method is designed, and the online system is used to update and perfect the inverse system model in real time. Finally, the virtual prototype model of the crawler is established, and the control effect of the adaptive inverse control method is verified by theoretical analysis and virtual prototype simulation.

Adaptive Inverse Fuzzy Decoupling Control of Bearingless Asynchronous Motor

2014 ◽  
Vol 703 ◽  
pp. 327-330
Author(s):  
Jian Dong Sun ◽  
Yu Xin Sun ◽  
Huang Qiu Zhu ◽  
Xian Xing Liu
Keyword(s):  
Control Method ◽  
Asynchronous Motor ◽  
Poor Performance ◽  
Decoupling Control ◽  
Matlab Simulation ◽  
Adaptive Inverse Control ◽  
Inverse Control ◽  
Highly Nonlinear ◽  
Static Performance ◽  
Control Of Linear Systems

The traditional control has good performance in the control of linear systems while has poor performance in the control of nonlinear systems. The bearingless asynchronous motor is a multivariable nonlinear system with high coupling. In this paper, the method of adaptive inverse control is proposed for these reasons. Firstly, the mathematical model of the bearingless asynchronous motor is built, and the possibility of the existence of the bearingless asynchronous motor system inverse model is explored. Secondly, since the object to be controlled is highly nonlinear and has high variability. In this paper, adaptive inverse fuzzy decoupling control is used to make up the deficiency of traditional adaptive inverse control. Finally, the Matlab simulation model is established. The simulation results show that the control method has good dynamic and static performance.

Adaptive Inverse Control of Hydro Electric Unit Based on Wavelet Neural Networks

2012 ◽  
Vol 591-593 ◽  
pp. 1200-1203
Author(s):  
Zhong Liao ◽  
Bin Yuan Ye
Keyword(s):  
Neural Networks ◽  
Control Method ◽  
Phase System ◽  
Minimum Phase ◽  
Wavelet Neural Networks ◽  
Adaptive Inverse Control ◽  
New Approach ◽  
Inverse Control ◽  
Unit System ◽  
Phase Systems

Due to the nonlinear, time-variable and non-minimum phase character of hydro electric unit system integrated with water, motor and power, a new adaptive inverse control method of hydro electric unit based on the function approximation ability of the wavelet analysis and the learning characteristic of neural network is presented. The algorithm and formulas and method of adaptive inverse control is studied. It approximates the model and its inversion of hydro electric unit by wavelet neural networks(WNN), and then through constructing an aim function of broad sense, which is effective to the nonlinear non-minimum phase system. Theory and simulation to for hydro electric unit system demonstrate that the control strategy can more effective improve the dynamic and stationary performance than those based on neural networks. It gives a new approach in control for hydro electric unit system besides offer a beneficial reference to the control of non-minimum phase systems.

Support vector machine-based fuzzy rules acquisition system

2009 ◽  
Vol 14 (5) ◽  
pp. 555-561
Author(s):  
Xi-xia Huang ◽  
Fan-huai Shi ◽  
Wei Gu ◽  
Shan-ben Chen
Keyword(s):  
Support Vector Machine ◽  
Fuzzy Rules ◽  
Acquisition System ◽  
Support Vector ◽  
Rules Acquisition

Study on Vibration Controller Based on Adaptive Inverse Method

2013 ◽  
Vol 765-767 ◽  
pp. 1979-1983
Author(s):  
Hao Li ◽  
Long Lei Dong ◽  
Wen Zhe Zhao
Keyword(s):  
Control System ◽  
Vibration Control ◽  
Digital Signal Processor ◽  
Control Method ◽  
Least Mean Square ◽  
Layer System ◽  
Software Environment ◽  
Hardware Platform ◽  
Adaptive Inverse Control ◽  
Inverse Control

In this paper, study of adaptive inverse controller based on nonlinear multi-degree-of-freedom (NLMDF) algorithm has been carried out. A vibration control system with TMS320F2812 as the hardware platform has been developed, which can realize waveform reproduction and spectrum control. An improved least mean square algorithm-NLMDF has been introduced to design the filter parameters in the adaptive inverse control and simulations have been carried out in Matlab software environment. Accordance with the requirements of the adaptive inverse control method, hardware platform of the vibration control system based on dual-Digital Signal Processor (DSP) architecture, has been designed; through abstraction of the driver layer, system layer and application layer of the vibration control system , software platform has been developed. The experiment results show that functionality and performance indicators of the system have reached the design requirements.

Sign in / Sign up

Export Citation Format

Share Document