Title :
Adaptive Repetitive Control for a Class of Nonlinearly Parametrized Systems
Author :
Sun, Mingxuan ; Ge, Shuzhi Sam
Author_Institution :
Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore
Abstract :
In this note, Lyapunov-based adaptive repetitive control is presented for a class of nonlinearly parametrized systems. Through the use of an integral Lyapunov function, the controller singularity problem is elegantly solved as it avoids the nonlinear parametrization from entering into the adaptive control and repetitive control. Global stability of the adaptive system and asymptotic convergence of the tracking error are established, and tracking error bounds are provided to quantify the control performance. Both partially and fully saturated learning laws are analyzed in detail, and compared analytically
Keywords :
Lyapunov methods; adaptive control; convergence; nonlinear control systems; stability; adaptive repetitive control; asymptotic convergence; controller singularity; global stability; integral Lyapunov function; nonlinearly parametrized system; tracking error; Adaptive control; Control systems; Error correction; Linear feedback control systems; Lyapunov method; Manipulator dynamics; Nonlinear control systems; Nonlinear systems; Programmable control; Sun; Adaptive control; nonlinear parametrization; repetitive control; saturated-learning;
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.2006.883028
