Output trajectory tracking using dynamic neural networks

Proceedings of the IEEE Conference on Decision and Control

Volumn 1, Issue , 2000, Pages 889-894

  Poznyak, Alex S ^a   Sanchez, Edgar N ^b   Palma, Orlando ^a   Yu, Wen ^a  

^a DEPARTAMENTO DE FÍSICA   (Mexico)

^b UNIDAD GUADALAJARA   (Mexico)

Author keywords

Dynamic neural network; Dynamic neuro control; Krasovskii functional; Robust neuro observer; Time delay

Indexed keywords

APPROXIMATION THEORY; ASYMPTOTIC STABILITY; DIFFERENTIAL EQUATIONS; DYNAMICS; ERRORS; LEARNING ALGORITHMS; MATRIX ALGEBRA; NONLINEAR CONTROL SYSTEMS; RICCATI EQUATIONS; ROBUSTNESS (CONTROL SYSTEMS); THEOREM PROVING; VECTORS;

DYNAMIC NEURAL NETWORKS; ESTIMATION ERROR; LYAPUNOV-KRASOVSKII TECHNIQUE; ROBUST ASYMPTOTIC NEURO OBSERVER;

NEURAL NETWORKS;

EID: 0034439114     PISSN: 01912216     EISSN: None     Source Type: Journal    
DOI: 10.1109/CDC.2000.912883     Document Type: Article

References (30)

1. Robust control of robots via linear estimated state feedback
2. Adaptively controlling nonlinear continuous-time systems using multilayer neural networks
3. A Luenberger-like observer for nonlinear system
4. Output feedback stabilization of fully linearizable systems
5. On the approximation realization of continuous mappings by the neural networks
6. A simple observer for nonlinear systems: Applications to bioreactors
7. Nonlinear observer design using dynamic recurrent neural networks
8. High-order neural network structures for identification of dynamical systems
9. Neural net robot controller with guaranteed tracking performance
10. Observing the state of linear system
11. Adaptive observer with arbitrary exponential rate of convergence for nonlinear system
12. Identification and control of dynamical systems using neural networks
13. High-gain observers in the state and parameter estimation of robots having elastic joins
14. Stable adaptive neural control scheme for nonlinear systems
15. Learning for dynamic neural networks
16. Robust identification by dynamic neural networks using sliding mode learning
17. On the robust design of sliding observers for linear systems
18. Further results on observer design problem
19. Use of asymptotic observer having high-gains in the state and parameter estimations
20. High-gains observer for nonlinear systems
21. Comparative study of nonlinear state observation technique
22. Indirect adaptive control via parallel dynamic neural networks
23. Least squares optimal control and algebraic Riccati equations
24. Feedback linearization using neural networks
25. Adaptive locally optimal control