Title :
Robust adaptive optimal control modification with large adaptive gain
Author :
Nguyen, Nhan T. ; Ishihara, Abraham K.
Author_Institution :
Ames Res. Center, Intell. Syst. Div., NASA, Moffett Field, CA, USA
Abstract :
A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on an optimal control formulation that minimizes the L2 norm of the tracking error. The optimality condition is used to derive the modification using the gradient method. The adaptive optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking performance with improved stability robustness. Simulations demonstrate the effectiveness of the proposed modification.
Keywords :
gradient methods; minimisation; model reference adaptive control systems; optimal control; robust control; L2 norm minimization; adaptive gain; gradient method; optimal control formulation; robust adaptive optimal control modification; standard model reference adaptive control; tracking error; Adaptive control; Approximation error; Error correction; Neural networks; Optimal control; Performance gain; Programmable control; Robust control; Robust stability; Uncertainty;
Conference_Titel :
American Control Conference, 2009. ACC '09.
Conference_Location :
St. Louis, MO
Print_ISBN :
978-1-4244-4523-3
Electronic_ISBN :
0743-1619
DOI :
10.1109/ACC.2009.5159904