Abstract
A decentralized adaptive control for trajectory tracking of robot manipulators is presented. The system is considered as a set of nonlinear subsystems with nonlinear uncertainties and interconnections. The tracking problem is tackled with decentralized controller. For each subsystem, an output feedback linearization is employed, and neural networks are used to compensate the system errors, the disturbances and the interconnections, which can simplify the design of the controller, improve the dynamic performance and make the system robust. Simulation results show that the system has a good tracking performance.
| Original language | English |
|---|---|
| Pages (from-to) | 1267-1270 |
| Number of pages | 4 |
| Journal | Xitong Fangzhen Xuebao / Journal of System Simulation |
| Volume | 18 |
| Issue number | 5 |
| State | Published - May 2006 |
Keywords
- Adaptive control
- Decentralized control
- Neural networks
- Robot manipulators
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