Function Approximation and Adaptive Control with Unstructured Uncertainty

@inproceedings{Nguyen2018FunctionAA,
  title={Function Approximation and Adaptive Control with Unstructured Uncertainty},
  author={Nhan T. Nguyen},
  year={2018}
}
  • N. Nguyen
  • Published 2018
  • Computer Science, Mathematics
This chapter presents the fundamental theories of least-squares function approximation and least-squares adaptive control of systems with unstructured uncertainty. The function approximation theory based on polynomials, in particular the Chebyshev orthogonal polynomials, and neural networks is presented. The Chebyshev orthogonal polynomials are generally considered to be optimal for function approximation of real-valued functions. The Chebyshev polynomial function approximation is therefore… 
1 Citations
Adaptive control systems with unstructured uncertainty and unmodelled dynamics: a relaxed stability condition
TLDR
Stability conditions of model reference adaptive control architectures in the presence of unstructured system uncertainties and unmodeled dynamics are analyzed and synthesized.

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