Name
Title | ||
|---|---|---|
Lower Extreme Carrying Exoskeleton Robot Adative Control Using Wavelet Neural Networks |
Abstract | ||
|---|---|---|
Using the wavelet neural networks, an adaptive control system, with two wavelet neural networks as controller and dynamics model identifier respectively, is developed for lower extreme carrying exoskeleton robot. Because the wavelet neural networks have the ability to approximate nonlinear functions and good advantage of time-frequency localization properties, this system can identify nonlinear system dynamic characters more precisely, and can map more complex control strategies. Results show that this control system is more effective than those based on normal controller, where the exoskeleton tracking precision is high and the operator feels very little torque. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/ICNC.2008.754 | ICNC |
Keywords | Field | DocType |
dynamics model identify,control system,lower extreme,neurocontrollers,time-frequency localization,exoskeleton robot adative control,adaptive control,intelligent robots,wavelet neural networks,exoskeleton tracking precision,wavelet neural network,nonlinear system,exoskeleton robot,approximate nonlinear function,lower extreme carrying exoskeleton robot,dynamics model identifier,adaptive control system,complex control strategy,normal controller,dynamic character,artificial neural networks,mathematical model,time frequency,actuators,torque | Control theory,Nonlinear system,Torque,Identifier,Control theory,Computer science,Exoskeleton,Control system,Adaptive control,Artificial neural network | Conference |
Volume | ISBN | Citations |
4 | 978-0-7695-3304-9 | 1 |
PageRank | References | Authors |
0.37 | 4 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiuxia Yang | 1 | 4 | 2.73 |
| Gui Lihua | 2 | 5 | 1.10 |
| Zhiyong Yang | 3 | 1 | 1.72 |
| Wenjin Gu | 4 | 13 | 5.63 |