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Adaptive Dynamic Inversion via Time-Scale Separation

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3 Author(s)
Naira Hovakimyan ; Dept. of Mech. Sci. & Eng., Univ. of Illinois at Urbana-Champaign, Urbana, IL ; Eugene Lavretsky ; Chengyu Cao

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.

Published in:

IEEE Transactions on Neural Networks  (Volume:19 ,  Issue: 10 )