Output tracking with constrained inputs via inverse optimal adaptive recurrent neural control

Engineering Applications of Artificial Intelligence

Volumn 21, Issue 4, 2008, Pages 591-603

  Ricalde, Luis J ^a   Sanchez, Edgar N ^b  

^a UNIVERSIDAD AUTÓNOMA DE YUCATÁN   (Mexico)

^b UNIDAD GUADALAJARA   (Mexico)

Author keywords

Adaptive control; Constrained inputs; Inverse optimal control; Output trajectory tracking; Recurrent neural networks

Indexed keywords

ADAPTIVE CONTROL SYSTEMS; CONSTRAINED OPTIMIZATION; INVERSE KINEMATICS; OPTIMAL CONTROL SYSTEMS; RECURRENT NEURAL NETWORKS;

CONSTRAINED INPUTS; INVERSE OPTIMAL CONTROL; OUTPUT TRAJECTORY TRACKING;

NONLINEAR EQUATIONS;

EID: 43749124365     PISSN: 09521976     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.engappai.2007.07.007     Document Type: Article

References (20)

1. Basar T., and Bernhard P. H-Infinity Optimal Control and Related Minimax Design Problems (1995), Birkhauser, Boston, USA
2. El-Farra N.H., and Christofides P.D. Integrating robustness, optimality and constraints in control of nonlinear processes. Chemical Engineering Science 56 (2001) 1841-1868
3. Hokimyan N., Rysdyk R., and Calise A. Dynamic neural networks for output feedback control. International Journal of Robust and Nonlinear Control 11 (2001) 23-39
4. Hopfield, J., 1984. Neurons with graded responses have collective computational properties like those of two state neurons. In: Proceedings of the National Academy of Sciences, USA, pp. 3088-3092.
5. Ioannou P., and Sun J. Robust Adaptive Control (1996), Prentice-Hall, Upper Saddle River, NJ, USA
6. Kapoor, N., Daoutidis, P., 1995. Stabilization of unstable systems with input constraints. In: Proceedings of the American Control Conference, vol. 5, pp. 3192-3196.
7. Khalil H. Nonlinear Systems. second ed. (1996), Prentice-Hall, Upper Saddle River, NJ, USA
8. Kosmatopoulos E.B., Christodoulou M.A., and Ioannou P.A. Dynamical neural networks that ensure exponential identification error convergence. Neural Networks 10 2 (1997) 299-314
9. Krstic M., and Deng H. Stabilization of Nonlinear Uncertain Systems (1998), Springer, New York, USA
10. Lin Y., and Sontag E. A universal formula for stabilization with bounded controls. Systems and Control Letters 16 (1991) 393-397
11. Low, K.S., Zhuang, H., 2003. Robust model predictive control of a motor drive with control input constraints. In: The Fifth International Conference on Power Electronics and Drive Systems, PEDS 2003, vol. 2, pp.1224-1228.
12. Narendra K.S., and Annaswamy A.M. Stable Adaptive Systems (1989), Prentice-Hall, Englewood Cliffs, NJ, USA
13. Narendra K.S., and Parthasarathy K. Identification and control of dynamical systems using neural networks. IEEE Transactions on Neural Networks 1 1 (1990) 4-27
14. Qiu, L., Miller, D.E., 2000. Stabilization of linear systems with input constraints. In: Proceedings of the 39th IEEE Conference on Decision and Control, 2000, vol. 4, pp. 3272-3277.
15. Ren, W., Beard, R.W., 2003. CLF-based tracking control for UAV kinematic models with saturation constraints. In: Proceedings.of the 42nd IEEE Conference on Decision and Control, vol. 4, pp. 3924-3929.
16. Rovitahkis G.A., and Christodoulou M.A. Adaptive Control with Recurrent High-Order Neural Networks (2000), Springer, New York, USA
17. Sanchez E.N., and Ricalde L.J. Chaos control and synchronization, with input saturation, via recurrent neural networks. Neural Networks 16 (2003) 711-717
18. Sanchez, E.N., Perez, J.P., Ricalde, L., 2002. Recurrent neural control for robot trajectory tracking. In: Proceedings of the 15th World Congress International Federation of Automatic Control, Barcelona, Spain.
19. Sanchez E.N., Perez J.P., and Ricalde L. Neural network control design for chaos control. In: Chen G., and Yu X. (Eds). Chaos Control: Theory and Applications (2003), Springer, Berlin
20. Sepulchre R., Jankovic M., and Kokotovic P.V. Constructive Nonlinear Control (1997), Springer, New York, USA