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Stable decentralized adaptive control design of robot manipulators using neural network approximations
- Source :
- Advanced Robotics. 17:369-383
- Publication Year :
- 2003
- Publisher :
- Informa UK Limited, 2003.
-
Abstract
- In this paper, we present a decentralized neural network (NN) adaptive technique for control of robot manipulators in the presence of unknown non-linear functions. Radial basis function NNs are used to approximate the non-linear functions to include the case of both parametric and dynamic uncertainty in each subsystem. The robustifying terms are added to the controllers to overcome the effects of the interconnections. The stability can be guaranteed by using a rigid proof. Finally, simulation is given to illustrate the effectiveness of the proposed algorithm.
- Subjects :
- Engineering
Adaptive control
Artificial neural network
business.industry
Stability (learning theory)
Robot manipulator
Control engineering
Decentralised system
Computer Science Applications
Human-Computer Interaction
Hardware and Architecture
Control and Systems Engineering
Control theory
Radial basis function
business
Software
Parametric statistics
Subjects
Details
- ISSN :
- 15685535 and 01691864
- Volume :
- 17
- Database :
- OpenAIRE
- Journal :
- Advanced Robotics
- Accession number :
- edsair.doi...........bbd722da692d6a27613bca86077e8c1f