Adaptive Feedback Linearization Using Efficient Neural Networks

  title={Adaptive Feedback Linearization Using Efficient Neural Networks},
  author={Aydin Yesildirek and Frank L. Lewis},
  journal={Journal of Intelligent and Robotic Systems},
For a class of single-input, single-output, continuous-time nonlinear systems, a feedback linearizing neural network (NN) controller is presented. Control action is used to achieve tracking performance. The controller is composed of a robustifying term and two neural networks adapted online to linearize the system by approximating two nonlinear functions. A stability proof is given in the sense of Lyapunov. No off-line weight learning phase is needed and initialization of the network weights is… CONTINUE READING
8 Citations
35 References
Similar Papers


Publications referenced by this paper.
Showing 1-10 of 35 references

Identification and control using neural network models: Design and stability analysis, Technical Report 91-09-01, Dept

  • M. M. Polycarpou, P. A. Ioannu
  • Elect. Eng. Sys., Univ. S. Cal.
  • 1991
Highly Influential
6 Excerpts

A bioreactor benchmark for adaptive network-based process

  • L. H. Ungar
  • Neural Networks for Control,
  • 1990
Highly Influential
4 Excerpts

The Organization of Behavior, Wiley, Reading/New York, 1949

  • D. O. Hebb
  • 1949
Highly Influential
4 Excerpts

Adaptive control of a class of nonlinear discrete - time systems using neural networks

  • F.-C. Chen, H. Khalil
  • IEEE Trans . Automat . Control
  • 1995

Adaptive control of a class of nonlinear discrete-time systems using neural networks, IEEE Trans

  • Chen, F.-C., H. Khalil
  • Automat. Control 40(5)
  • 1995
1 Excerpt

Robust control of a continuous stirred-tank reactor

  • K. Liu, F. L. Lewis
  • in: Proc. American Control Conf.,
  • 1994
1 Excerpt

Similar Papers

Loading similar papers…