- Course overview:
Introduction, Motivating Examples, Current state of the art.
- Review of Lyapunov Stability Theory:
- Nonlinear systems and equilibrium points.
- Linearization.
- Lyapunov direct method.
- LaSalle extensions.
- Barbalat Lemma and Lyapunov-like Lemma.
- Uniform Ultimate Boundedness by Lyapunov Extension.
- Adaptive control architectures :
- Basic concepts.
- Design approach: Direct vs. indirect.
- Certainty Equivalence Principle
- Model Reference Adaptive Control, (MRAC)
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Augmentation of a nominal design
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Using dynamic inversion
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Adaptive backstepping
- Artificial Neural Networks, (NN)
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Universal approximation properties
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Using sigmoids
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Using Radial Basis Functions, (RBF)
- Enforcing robustness to parametric and non-Parametric uncertainties
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Dead-zone
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Sigma modification
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E – modification d. Projection operator
- Adaptive NeuroControl
- On-line parameter estimation, parameter convergence, and Persistency of Excitation (PE) conditions
- Design Examples
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Adaptive Augmentation of an LQR controller with integral action
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Adaptive Reconfigurable Flight Control using RBF NN-s
Main Textbooks
- J.J. Slotine, W. Li,
Applied Nonlinear Control,
Prentice Hall, 1995.
- H.K. Khalil,
Nonlinear Systems, 3rd Edition,
Prentice Hall, New Jersey, 2002.
Additional / Supplementary Textbooks
- M. Krstic, I. Kanellakopoulos, P. Kokotovic,
Nonlinear and Adaptive Control Design,
John Wiley & Sons, New York, 1995.
- K. Narendra, and A. Annaswamy,
Stable Adaptive Control,
Prentice Hall, 1989.
- S.S. Sastry and M. Bodson,
Adaptive Control: Stability, Convergence and Robustness,
Prentice Hall, 1989.
- P. Ioannou, J. Sun,
Robust Adaptive Control,
Prentice Hall, New Jersey, 1996.
- F. Lewis, S. Jagannathan, S., A. Yesildirek,
Neural Network Control of Robot Manipulators and Nonlinear Systems,
Taylor & Francis, 1998.
- R.Marino and P.Tomei,
Nonlinear Control Design: Geometric, Adaptive, Robust,
Prentice Hall, New Jersey, 1995.
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