An SPR approach for adaptive output feedback control with neural networks

Anthony J. Calise, Naira Hovakimyan, Moshe Idan

Research output: Contribution to journalConference article

Abstract

A direct adaptive output feedback control design procedure is developed for highly uncertain nonlinear systems, that does not rely on state estimation. The approach is also applicable to systems of unknown, but bounded dimension. This includes systems with both parametric uncertainties and unmodelled dynamics. This result is achieved by extending the universal function approximation property of linearly parameterized neural networks to model unknown system dynamics from input/output data. The network weight adaptation rule is derived from Lyapunov stability analysis, that guarantees boundedness of the NN weights and the system tracking errors. Numerical simulations of an output feedback controlled Van der Pol oscillator, coupled with a linear oscillator, are used to illustrate the practical potential of the theoretical results.

Original languageEnglish (US)
Pages (from-to)3134-3139
Number of pages6
JournalProceedings of the IEEE Conference on Decision and Control
Volume4
StatePublished - Dec 1 2001
Externally publishedYes
Event40th IEEE Conference on Decision and Control (CDC) - Orlando, FL, United States
Duration: Dec 4 2001Dec 7 2001

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Output Feedback Control
State estimation
Feedback control
Nonlinear systems
Dynamical systems
Neural Networks
Universal Approximation
Neural networks
Feedback
Unmodeled Dynamics
Unknown
Van Der Pol Oscillator
Universal Function
Uncertain Nonlinear Systems
Parametric Uncertainty
Lyapunov Stability
Computer simulation
Function Approximation
Approximation Property
Output Feedback

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

Cite this

An SPR approach for adaptive output feedback control with neural networks. / Calise, Anthony J.; Hovakimyan, Naira; Idan, Moshe.

In: Proceedings of the IEEE Conference on Decision and Control, Vol. 4, 01.12.2001, p. 3134-3139.

Research output: Contribution to journalConference article

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