TY - JOUR
T1 - Achieving Asymptotic Tracking Yet Accommodating More Generalized Performance Specifications via Approximation-free Approach
AU - CAO, Lan
AU - HUANG, Xiucai
AU - LV, Maolong
AU - SONG, Yongduan
PY - 2026/2/2
Y1 - 2026/2/2
N2 - This article presents an asymptotic tracking control framework that accommodates generalized performance specifications for a class of unknown strict-feedback nonlinear systems. The proposed method, which is approximation-free, confines transient performance within a preassigned more flexible region (rather than merely a funnel one) by employing unified performance functions (instead of monotonic functions) to facilitate the output tracking error transformation, the underlying problem is reduced to purely stabilization control for the newly transformed system. By integrating the robust integral of the sign of error (RISE) technique with the backstepping approach, a continuous control law is developed that ensures asymptotic tracking and robustness against uncertainties and disturbances without employing neural or fuzzy approximators, which not only guarantees the boundedness of the closed-loop signals, but also remains the computation complexity at a low level. The effectiveness and superiority of the proposed algorithm are demonstrated through simulation.
AB - This article presents an asymptotic tracking control framework that accommodates generalized performance specifications for a class of unknown strict-feedback nonlinear systems. The proposed method, which is approximation-free, confines transient performance within a preassigned more flexible region (rather than merely a funnel one) by employing unified performance functions (instead of monotonic functions) to facilitate the output tracking error transformation, the underlying problem is reduced to purely stabilization control for the newly transformed system. By integrating the robust integral of the sign of error (RISE) technique with the backstepping approach, a continuous control law is developed that ensures asymptotic tracking and robustness against uncertainties and disturbances without employing neural or fuzzy approximators, which not only guarantees the boundedness of the closed-loop signals, but also remains the computation complexity at a low level. The effectiveness and superiority of the proposed algorithm are demonstrated through simulation.
U2 - 10.1109/TAC.2026.3660175
DO - 10.1109/TAC.2026.3660175
M3 - Journal Article (refereed)
SN - 0018-9286
JO - IEEE Transactions on Automatic Control
JF - IEEE Transactions on Automatic Control
ER -