Discrete-time tuning of neural network controllers for nonlinear

Details Discrete-time tuning of neural network controllers for nonlinear Discrete-time tuning of neural network controllers for nonlinear

1997-03-19

2000-05-16

Hafiz, Tariq R.

Data processing: artificial intelligence

Neural network

Learning task

706 22, 706 31, 706 39, 706103, 706106, 36414803, G06F 1518

Patent

active

060649976

ABSTRACT:
A family of novel multi-layer discrete-time neural net controllers is presented for the control of an multi-input multi-output (MIMO) dynamical system. No learning phase is needed. The structure of the neural net (NN) controller is derived using a filtered error/passivity approach. For guaranteed stability, the upper bound on the constant learning rate parameter for the delta rule employed in standard back propagation is shown to decrease with the number of hidden-layer neurons so that learning must slow down. This major drawback is shown to be easily overcome by using a projection algorithm in each layer. The notion of persistency of excitation for multilayer NN is defined and explored. New on-line improved tuning algorithms for discrete-time systems are derived, which are similar to e-modification for the case of continuous-time systems, that include a modification to the learning rate parameter plus a correction term. These algorithms guarantee tracking as well as bounded NN weights. An extension of these novel weight tuning updates to NN with an arbitrary number of hidden layers is discussed. The notions of discrete-time passive NN, dissipative NN, and robust NN are introduced.

REFERENCES:
patent: 5119468 (1992-06-01), Owens
patent: 5121467 (1992-06-01), Skeirik
patent: 5159660 (1992-10-01), Lu et al.
patent: 5471381 (1995-11-01), Khan
patent: 5513098 (1996-04-01), Spall et al.
patent: 5566065 (1996-10-01), Hansen et al.
Jagannathan et al, "Identification of a Class of Nonlinear Dynamical Systems Using Multilayer Neural Networks", 1994 IEEE International Symposium on Intelligent Control, Aug. 1994.
Jagannathan et al, "Multilayer Neural Network Controller for a class of Nonlinear Systems", Proceeding of the International Symposium on Control, IEEE, Aug. 1995.
Vidyasagar, M. "Nonlinear Systems Analysis," Prentice Hall, Inc. Englewood, New Jersey, 1993.
F. Chen, H.K. Khalil, "Adaptive control of nonlinear systems using neural networks," Int. J. Control, 55(6):1299-1317, 1992.
G.C. Goodwin, K.S. Sin, "Adaptive Filtering, Prediction and Control," Prentice-Hall Inc., Englewood Cliffs, NJ, 1984.
S. Jagannathan, F.L. Lewis, "Multilayer Discrete-time neural net controller with guaranteed performance," IEEE Transaction on Neural Networks 7(1):107-130, Jan. 1996.
I.D. Landau, "Evolution of adaptive control," ASME Journal of Dynamic Systems, Measurements, and Control, 115:381-391, Jun. 1993.
I.D. Landau, "Adaptive Control: The Model Reference Approach," Marcel Dekker, Inc., 1979.
A.U. Levine, K.S. Narendra, "Control of nonlinear dynamical systems using neural networks: Controllability and stabilization," IEEE Trans. Neural Networks, 4(2), Mar. 1993.
F.L. Lewis, K. Liu, A. Yesildirek, "Multilayer Neural net robot controller with guaranteed tracking performance," IEEE. Trans. on Neural Networks, Mar. 1996.
K.S. Narendra, A.M. Annaswamy, "A new adaptive law for robust adaptation without persistent adaptation," IEEE Trans. Automatic Control, AC-32(2):134-145, Feb. 1987.
K.S. Narendra, K. Parthasarathy, "Identification and control of dynamical systems using neural networks," IEEE Trans. Neural Networks, 1:4-27, Mar. 1990.
R. Ortega, L. Praly, I.D. Landau, "Robustness of discrete-time direct adaptive controllers," IEEE Trans. Automatic Control, AC-30(12):1179-1187, Dec. 1985.
Sadegh, N., "A Perceptron Network for Functional Identification and Control of Nonlinear Systems," IEEE Transactions on Neural Networks, 4(6):982-988, 1993.
Sanner et al., "Gaussian Networks for Direct Adaptive Control," IEEE Transactions on Neural Networks, 3(6):837-863, Nov. 1992.
R.M. Sanner, J.J.E. Slotine, "Stable adaptive control and recursive identification using radial gaussian networks," Proc. IEEE Conf. Decision and Control, Brighton, 1991.
H.J. Sira-Ramirez, S.H. Zak, "The adaptation of perceptrons with applications to inverse dynamics identification of unknown dynamic systems," IEEE Trans. Systems, Man, and Cybernetics, 21(3), May/Jun. 1991.
B. Widrow, M. Lehr, "30 Years of Adaptive Neural Networks: Perceptrons, Madaline, and Backpropagation," Proceedings of the IEEE, 78(9):1415-1442, Sep. 1990.

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