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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Zhi Wang Shiqiang Zhu Qingcheng Chen Xuequn Zhang Yang Song |
| Copyright Year | 2015 |
| Description | Author affiliation: State Key Lab. of Fluid Power & Control, Zhejiang Univ., Hangzhou, China (Zhi Wang; Shiqiang Zhu; Qingcheng Chen; Xuequn Zhang) || Sanlian (Shanghai) Group, Shanghai, China (Yang Song) |
| Abstract | Exoskeleton has drawn a great deal of attention recently because it can augment human strength and track human's motion. The objective of this paper is to enhance the performance of the electro-hydraulic servo system of the lower-limb exoskeleton, including model uncertainties and load disturbance. To accomplish the objective, a hybrid control method, combining sliding mode controller with RBF neural network, and disturbance observer is presented. The sliding mode controller is the main controller to control the electro-hydraulic servo system to track the desired trajectory. The RBF neural network is used to compensate the model uncertainties, and the disturbance observer is designed to deduce the external unknown load force. The simulation results show that the electro-hydraulic Servo System of the exoskeleton can achieve a better tracking performance with the proposed controller. |
| Starting Page | 79 |
| Ending Page | 83 |
| File Size | 279587 |
| Page Count | 5 |
| File Format | |
| e-ISBN | 9781479983896 |
| DOI | 10.1109/ICIEA.2015.7334088 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-06-15 |
| Publisher Place | New Zealand |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Servomotors Neural networks Exoskeletons Observers Valves Sensors Force disturbance observer lower-limb exoskeleton sliding mode control RBF neural network |
| Content Type | Text |
| Resource Type | Article |
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