Nonlinear adaptive control using neural networks and multiple models

In this paper, adaptive control of a class of nonlinear discrete time dynamical systems with boundedness of all signals is established by using a linear robust adaptive controller and a neural network based nonlinear adaptive controller, and switching between them by a suitably defined switching law. The linear controller, when used alone, assures boundedness of all the signals but not satisfactory performance. The nonlinear controller may result in improved response, but may also result in instability. By using a switching scheme, it is demonstrated that improved performance and stability can be simultaneously achieved.

[1]  Chen-Chung Liu,et al.  Adaptively controlling nonlinear continuous-time systems using multilayer neural networks , 1994, IEEE Trans. Autom. Control..

[2]  F. Lewis,et al.  Discrete-time neural net controller for a class of nonlinear dynamical systems , 1996, IEEE Trans. Autom. Control..

[3]  Kumpati S. Narendra,et al.  Adaptive control of discrete-time systems using multiple models , 2000, IEEE Trans. Autom. Control..

[4]  Kumpati S. Narendra,et al.  Nonlinear adaptive control using neural networks and multiple models , 2001, Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No.00CH36334).

[5]  Marios M. Polycarpou,et al.  Stable adaptive neural control scheme for nonlinear systems , 1996, IEEE Trans. Autom. Control..

[6]  J. Farrell,et al.  Nonlinear adaptive control using networks of piecewise linear approximators , 1999, Proceedings of the 38th IEEE Conference on Decision and Control (Cat. No.99CH36304).

[7]  Kumpati S. Narendra,et al.  Adaptive control using multiple models , 1997, IEEE Trans. Autom. Control..

[8]  Graham C. Goodwin,et al.  Adaptive filtering prediction and control , 1984 .

[9]  Hassan K. Khalil,et al.  Adaptive control of a class of nonlinear discrete-time systems using neural networks , 1995, IEEE Trans. Autom. Control..

[10]  K. Narendra,et al.  Identification and control of a nonlinear dynamical system based on its linearization. II , 2002, Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301).

[11]  Kevin M. Passino,et al.  Decentralized adaptive control of nonlinear systems using radial basis neural networks , 1999, IEEE Trans. Autom. Control..

[12]  K. S. Narendra,et al.  Neural networks for control theory and practice , 1996, Proc. IEEE.

[13]  Bernard Delyon,et al.  Nonlinear black-box models in system identification: Mathematical foundations , 1995, Autom..

[14]  Anuradha M. Annaswamy,et al.  Stable Adaptive Systems , 1989 .

[15]  Frank L. Lewis,et al.  Multilayer discrete-time neural-net controller with guaranteed performance , 1996, IEEE Trans. Neural Networks.

[16]  Kumpati S. Narendra,et al.  On a new approach to the design of tracking controllers for nonlinear dynamical systems , 1999, Proceedings of the 1999 American Control Conference (Cat. No. 99CH36251).

[17]  Anuradha M. Annaswamy,et al.  Adaptive control of nonlinear dynamic systems using θ-adaptive neural networks , 1997, Autom..

[18]  Deepak Shukla,et al.  Multiple neural-network-based adaptive controller using orthonormal activation function neural networks , 1999, IEEE Trans. Neural Networks.

[19]  Ken-ichi Funahashi,et al.  On the approximate realization of continuous mappings by neural networks , 1989, Neural Networks.

[20]  Kwanghee Nam.  Stabilization of feedback linearizable systems using a radial basis function network , 1999, IEEE Trans. Autom. Control..

[21]  Robert M. Sanner,et al.  Gaussian Networks for Direct Adaptive Control , 1991, 1991 American Control Conference.

[22]  Kumpati S. Narendra,et al.  Issues in the application of neural networks for tracking based on inverse control , 1999, IEEE Trans. Autom. Control..