Neuroadaptive control of elastic-joint robots using robust performance enhancement

Robotica

Volumn 19, Issue 6, 2001, Pages 619-629

  Macnab, C J B ^a   D'Eleuterio, G M T ^a  

^a UNIVERSITY OF TORONTO   (Canada)

Author keywords

Elastic joint robots; Neural network; Neuroadaptive control; Performance enhancement

Indexed keywords

ADAPTIVE CONTROL SYSTEMS; ASSOCIATIVE STORAGE; DEGREES OF FREEDOM (MECHANICS); LEARNING SYSTEMS; LYAPUNOV METHODS; MANIPULATORS; MATHEMATICAL MODELS; PERFORMANCE; RADIAL BASIS FUNCTION NETWORKS; ROBUSTNESS (CONTROL SYSTEMS); UNIVERSAL JOINTS;

CEREBELLAR MODEL ARITHMETIC COMPUTER; ELASTIC JOINT ROBOTS; NEUROADAPTIVE CONTROL;

ROBOTICS;

EID: 0035517163     PISSN: 02635747     EISSN: None     Source Type: Journal    
DOI: 10.1017/s0263574799002155     Document Type: Article

References (23)

1. A method to design adaptive controllers for flexible joint robots
2. Robust tracking of rigid-link flexible-joint electrically-driven robots
3. Global tracking controllers for flexible-joint manipulators: A comparative study
4. Robust neural network control of flexible-joint robots
5. A new adaptive law for robust adaptive control without persistance of excitation
6. A new approach to manipulator control: The cerebellar model articulation controller (CMAC)
7. Data storage in the cerebellar model articulation controller (CMAC)
8. Sensor-based control of robotic manipulators using a general learning algorithm
9. Real-time dynamic control of an industrial manipulator using a neural-network based learning controller
10. A neural network paradigm for robotic control
11. Stable, on-line learning using CMACs for neuroadaptive tracking control of flexible-joint manipulators
12. On the adaptive control of robot manipulators
13. Uncertain dynamics systems-Lyapunov min-max approach
14. Continuous state feedback guaranteeing uniform ultimate boundedness for uncertain dynamic systems
15. Adaptive robot control: A new perspective
16. Stability and convergence of neurologic model based robotic controllers
17. Guassian networks for direct adaptive control