Stable auto-tuning of the adaptation gain for continuous-time nonlinear systems

Hazem Nounou, Kevin M. Passino

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

In direct adaptive control, the adaptation mechanism attempts to adjust a parameterized nonlinear controller to approximate an ideal controller. In the indirect case, however, we approximate parts of the plant dynamics that are used by a feedback controller to cancel the system nonlinearities. In both cases, "approximators" such as linear mappings, polynomials, fuzzy systems, or neural networks can be used as either the parameterized nonlinear controller or identifier model. In this paper, we present an algorithm to tune the adaptation gain for a gradient-based hybrid update law used for a class of nonlinear continuous-time systems in both direct and indirect cases. In our proposed algorithm, the adaptation gain is obtained by minimizing the instantaneous control energy.

Original languageEnglish
Pages (from-to)2037-2042
Number of pages6
JournalProceedings of the IEEE Conference on Decision and Control
Volume3
Publication statusPublished - 2001
Externally publishedYes

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Auto-tuning
Continuous-time Systems
Nonlinear systems
Nonlinear Systems
Tuning
Controller
Controllers
Polynomial Mapping
Continuous time systems
Control nonlinearities
Cancel
Fuzzy systems
Power control
Fuzzy Systems
Adaptive Control
Instantaneous
Update
Polynomials
Nonlinearity
Neural Networks

ASJC Scopus subject areas

  • Chemical Health and Safety
  • Control and Systems Engineering
  • Safety, Risk, Reliability and Quality

Cite this

Stable auto-tuning of the adaptation gain for continuous-time nonlinear systems. / Nounou, Hazem; Passino, Kevin M.

In: Proceedings of the IEEE Conference on Decision and Control, Vol. 3, 2001, p. 2037-2042.

Research output: Contribution to journalArticle

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