K. S. Narendra, “Adaptive control of dynamical systems using neural networks”, in Handbook of intelligent control: neural, fuzzy and adaptive approaches

O. Nerrand, L. Personnaz, and G. Dreyfus, “Nonlinear recursive identification and control by neural networks: a general framework”, Proceedings of the 2nd European Control Conference, pp.93-98, 1993.

K. S. Narendra and S. Mukhopadhyay, Adaptive control of nonlinear multivariable systems using neural networks, Neural Networks, vol.7, issue.5, pp.737-752, 1994.
DOI : 10.1016/0893-6080(94)90096-5

R. Sanner and J. Slotine, Stable Adaptive Control of Robot Manipulators Using ???Neural??? Networks, Neural Computation, vol.14, issue.5, pp.4-753, 1995.
DOI : 10.1109/72.165591

F. Chen and H. K. Khalil, Adaptive control of a class of nonlinear discrete-time systems using neural networks, IEEE Transactions on Automatic Control, vol.40, issue.5, pp.791-801, 1995.
DOI : 10.1109/9.384214

A. U. Levin and K. S. Narendra, Control of nonlinear dynamical systems using neural networks: controllability and stabilization, IEEE Transactions on Neural Networks, vol.4, issue.2, pp.192-206, 1993.
DOI : 10.1109/72.207608

I. Rivals, L. Personnaz, and G. , Dreyfus and D. Canas, “Real-time control of an autonomous vehicle: a neural network approach to the path following problem”, 5th International Conference on Neural Networks and their Applications, pp.219-229, 1993.

M. Morari and E. Zafiriou, Robust process control, 1989.

G. C. Economou, M. Morari, and B. O. Palsson, Internal Model Control: extension to nonlinear system, Industrial & Engineering Chemistry Process Design and Development, vol.25, issue.2, pp.403-411, 1986.
DOI : 10.1021/i200033a010

J. Calvet and Y. Arkun, Feedforward and feedback linearization of nonlinear system and its implementation using internal model control (IMC), Industrial & Engineering Chemistry Research, vol.27, issue.10, pp.1822-1831, 1988.
DOI : 10.1021/ie00082a015

J. Alvarez, “An internal-model controller for nonlinear systems”, Proceedings of the 3rd European Control Conference, pp.301-306, 1995.

D. C. Psichogios and L. H. Ungar, Direct and indirect model based control using artificial neural networks, Industrial & Engineering Chemistry Research, vol.30, issue.12, pp.2564-2573, 1991.
DOI : 10.1021/ie00060a009

K. J. Hunt and D. Sbarbaro, Neural networks for nonlinear internal model control, IEE Proceedings D Control Theory and Applications, vol.138, issue.5, pp.431-438, 1991.
DOI : 10.1049/ip-d.1991.0059

K. J. Hunt and D. Sbarbaro, “Studies in neural network based control”, in Neural networks for control and systems, pp.94-122, 1992.

J. C. Kalkkuhl and K. J. Hunt, DISCRETE-TIME NEURAL MODEL STRUCTURES FOR CONTINUOUS-TIME NONLINEAR SYSTEMS: FUNDAMENTAL PROPERTIES AND CONTROL ASPECTS, Neural Adaptive Control Technology, pp.3-40, 1996.
DOI : 10.1142/9789812830388_0001

G. Cybenko, Approximation by superpositions of a sigmoidal function, Mathematics of Control, Signals, and Systems, vol.27, issue.4, pp.303-314, 1989.
DOI : 10.1007/BF02551274

K. Hornik, M. Stinchcombe, and H. White, Multilayer feedforward networks are universal approximators, “Multilayer feedforward networks are universal approximators”, pp.359-366, 1989.
DOI : 10.1016/0893-6080(89)90020-8

O. Nerrand, P. Roussel-ragot, D. Urbani, L. Personnaz, and G. Dreyfus, Training recurrent neural networks: why and how? An illustration in dynamical process modeling, IEEE Transactions on Neural Networks, vol.5, issue.2, pp.178-184, 1994.
DOI : 10.1109/72.279183

I. Rivals and L. Personnaz, “Black-box modeling with state-space neural networks”, in Neural Adaptive Control Technology, pp.237-264, 1996.

M. I. Jordan, The learning of representations for sequential performance, Doctoral Dissertation, 1985.

D. E. Rumelhart, G. E. Hinton, and R. J. Williams, “Learning internal representations by error back-propagation”, in Parallel Distributed Processing: explorations in the microstructure of cognition, pp.318-362, 1986.

O. Nerrand, P. Roussel-ragot, L. Personnaz, and G. Dreyfus, Neural Networks and Nonlinear Adaptive Filtering: Unifying Concepts and New Algorithms, Neural Computation, vol.5, issue.2, pp.2-165, 1993.
DOI : 10.1162/neco.1990.2.4.490

L. Jin, P. N. Nikiforuk, and M. M. Gupta, “Diagonal lyapunov functions for global stability of discrete-time neural networks”, Neural Network World 1/95, pp.71-79, 1995.

K. Tanaka, An approach to stability criteria of neural-network control systems, IEEE Transactions on Neural Networks, vol.7, issue.3, pp.629-642, 1996.
DOI : 10.1109/72.501721

S. Monaco and D. Normand-cyrot, “Minimum-phase nonlinear discrete-time systems and feedback stabilisation”, Proceedings of the 26th Conference on Decision and Control, pp.979-986, 1987.

H. Nijmeijer and A. J. , Van Der Schaft, Nonlinear dynamical control systems, 1990.

G. C. Goodwin and K. S. Sin, Adaptive filtering prediction and control, 1984.

S. Abu, A. Ata, and . Coic, “Commande prédictive par inversion: application aux systèmes non-linéaires”, DRET contract n°87, 1988.

Ü. Kotta, Inversion method in the discrete-time nonlinear control systems synthesis problems, 1995.
DOI : 10.1007/3-540-19966-7

J. Renders, M. Saerens, and H. Bersini, Adaptive Neurocontrol of a Certain Class of MIMO Discrete-Time Processes Based on Stability Theory, Neural Network Engineering in Dynamic Control Systems, pp.43-60, 1995.
DOI : 10.1007/978-1-4471-3066-6_3

I. Rivals, Modélisation et commande de processus par réseaux de neurones ; application au pilotage d’un véhicule autonome, Thèse de Doctorat de l’Université Paris, 1995.

I. Rivals and L. Personnaz, Internal model control using neural networks, Proceedings of IEEE International Symposium on Industrial Electronics, pp.109-114, 1996.
DOI : 10.1109/ISIE.1996.548401

URL : https://hal.archives-ouvertes.fr/hal-00797666

I. Rivals, D. Canas, L. Personnaz, and G. Dreyfus, Modeling and control of mobile robots and intelligent vehicles by neural networks, Proceedings of the Intelligent Vehicles '94 Symposium, pp.137-142, 1994.
DOI : 10.1109/IVS.1994.639489