TY - JOUR
T1 - Adaptive dynamic inversion via time-scale separation
AU - Hovakimyan, Naira
AU - Lavretsky, Eugene
AU - Cao, Chengyu
N1 - Funding Information:
Manuscript received July 8, 2007; revised January 29, 2008; accepted June 4, 2008. First published August 26, 2008; current version published October 8, 2008. This work was supported by the United States Air Force under Contracts FA9550-05-1-0157 and FA9550-04-C-0047. N. Hovakimyan is with the Department of Mechanical Science and Engineering of University of Illinois at Urbana-Champaign, Urbana, IL 61801 USA (e-mail: [email protected]). E. Lavretsky is with Phantom Works, The Boeing Company, Huntington Beach, CA 92649 USA (e-mail: [email protected]). C. Cao is with the University of Connecticut, Storrs, CT 06269 USA (e-mail: [email protected]). Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/TNN.2008.2001221
PY - 2008
Y1 - 2008
N2 - 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.
AB - 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.
KW - Adaptive control
KW - Nonaffine systems
KW - Time-scale separation
KW - Ultimate boundedness
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U2 - 10.1109/TNN.2008.2001221
DO - 10.1109/TNN.2008.2001221
M3 - Article
C2 - 18842475
AN - SCOPUS:54349110791
SN - 1045-9227
VL - 19
SP - 1702
EP - 1711
JO - IEEE Transactions on Neural Networks
JF - IEEE Transactions on Neural Networks
IS - 10
ER -