Adaptive dynamic inversion via time-scale separation

Naira Hovakimyan; Eugene Lavretsky; Chengyu Cao

doi:10.1109/TNN.2008.2001221

Adaptive dynamic inversion via time-scale separation

Naira Hovakimyan, Eugene Lavretsky, Chengyu Cao

Research output: Contribution to journal › Article

Abstract

This paper presents a full state feedback adaptive dynamic inversion method for uncertain systems that depend nonlinearly upon the control input. Using a specialized set of basis functions that respect the monotonic property of the system nonlinearities with respect to control input, a state predictor is defined for derivation of the adaptive laws. The adaptive dynamic inversion controller is defined as a solution of a fast dynamical equation, which achieves time-scale separation between the state predictor and the controller dynamics. Lyapunov-based adaptive laws ensure that the predictor tracks the state of the nonlinear system with bounded errors. As a result, the system state tracks the desired reference model with bounded errors. Benefits of the proposed design method are demonstrated using Van der Pol dynamics with nonlinear control input.

Original language	English (US)
Pages (from-to)	1702-1711
Number of pages	10
Journal	IEEE Transactions on Neural Networks
Volume	19
Issue number	10
DOIs	https://doi.org/10.1109/TNN.2008.2001221
State	Published - Aug 28 2008

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Keywords

Adaptive control
Nonaffine systems
Time-scale separation
Ultimate boundedness

ASJC Scopus subject areas

Software
Computer Science Applications
Computer Networks and Communications
Artificial Intelligence

Cite this

Hovakimyan, N., Lavretsky, E., & Cao, C. (2008). Adaptive dynamic inversion via time-scale separation. IEEE Transactions on Neural Networks, 19(10), 1702-1711. https://doi.org/10.1109/TNN.2008.2001221

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Access to Document

10.1109/TNN.2008.2001221