Name
Title | ||
|---|---|---|
Adaptive Impedance Control for Upper-Limb Rehabilitation Robot Using Evolutionary Dynamic Recurrent Fuzzy Neural Network |
Abstract | ||
|---|---|---|
Control system implementation is one of the major difficulties in rehabilitation robot design. A newly developed adaptive impedance controller based on evolutionary dynamic fuzzy neural network (EDRFNN) is presented, where the desired impedance between robot and impaired limb can be regulated in real time according to the impaired limb's physical recovery condition. Firstly, the impaired limb's damping and stiffness parameters for evaluating its physical recovery condition are online estimated by using a slide average least squares (SALS)identification algorithm. Then, hybrid learning algorithms for EDRFNN impedance controller are proposed, which comprise genetic algorithm (GA), hybrid evolutionary programming (HEP) and dynamic back-propagation (BP) learning algorithm. GA and HEP are used to off-line optimize DRFNN parameters so as to get suboptimal impedance control parameters. Dynamic BP learning algorithm is further online fine-tuned based on the error gradient descent method. Moreover, the convergence of a closed loop system is proven using the discrete-type Lyapunov function to guarantee the global convergence of tracking error. Finally, simulation results show that the proposed controller provides good dynamic control performance and robustness with regard to the change of the impaired limb's physical condition. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/s10846-010-9462-3 | Journal of Intelligent and Robotic Systems |
Keywords | Field | DocType |
Rehabilitation robot,Dynamic recurrent fuzzy neural network,Genetic algorithms,Hybrid evolutionary programming,On-line identification,Adaptive impedance control | Gradient descent,Control theory,Control theory,Control engineering,Robustness (computer science),Impedance control,Engineering,Control system,Artificial neural network,Evolutionary programming,Genetic algorithm | Journal |
Volume | Issue | ISSN |
62 | 3-4 | 0921-0296 |
Citations | PageRank | References |
15 | 1.16 | 20 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guozheng Xu | 1 | 52 | 6.89 |
| Aiguo Song | 2 | 546 | 86.46 |
| Huijun Li | 3 | 76 | 14.37 |