TY - JOUR
T1 - A new adaptive designated-time stabilizing strategy for uncertain time-varying nonlinear systems
AU - Sun, Zong Yao
AU - Li, Jiao Jiao
AU - Wen, Changyun
AU - Chen, Chih Chiang
N1 - Publisher Copyright:
IEEE
PY - 2024
Y1 - 2024
N2 - This paper explores the adaptive designated-time stabilizing strategy for a class of uncertain time-varying nonlinear systems. The inspiration is driven by two challenging issues that remain unsolved in the field of prescribed-time stabilization: i) the singularity induced by infinity control magnitudes at the prescribed time instant and ii) the incapability of driving state behavior after the prescribed time. To tackle the challenges, we formulate a hybrid stabilizing controller by utilizing both the state scaling technique and a finite-time stabilizing process, which is bounded on the whole-time horizon and guarantees the existence of the solutions of the closed-loop system. Superior to the current prescribed-time stabilization results, the proposed strategy is not only able to ensure that the states of the closed-loop system converge to a compact set within a designated time and belongs to the set afterward, and enjoys finite-time convergence ultimately, but also manipulate intricate dynamics and parameter uncertainties effectively. Finally, simulation examples are given to demonstrate the validity of the proposed strategy.
AB - This paper explores the adaptive designated-time stabilizing strategy for a class of uncertain time-varying nonlinear systems. The inspiration is driven by two challenging issues that remain unsolved in the field of prescribed-time stabilization: i) the singularity induced by infinity control magnitudes at the prescribed time instant and ii) the incapability of driving state behavior after the prescribed time. To tackle the challenges, we formulate a hybrid stabilizing controller by utilizing both the state scaling technique and a finite-time stabilizing process, which is bounded on the whole-time horizon and guarantees the existence of the solutions of the closed-loop system. Superior to the current prescribed-time stabilization results, the proposed strategy is not only able to ensure that the states of the closed-loop system converge to a compact set within a designated time and belongs to the set afterward, and enjoys finite-time convergence ultimately, but also manipulate intricate dynamics and parameter uncertainties effectively. Finally, simulation examples are given to demonstrate the validity of the proposed strategy.
UR - http://www.scopus.com/inward/record.url?scp=85200262814&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85200262814&partnerID=8YFLogxK
U2 - 10.1109/TAC.2024.3435913
DO - 10.1109/TAC.2024.3435913
M3 - Article
AN - SCOPUS:85200262814
SN - 0018-9286
SP - 1
EP - 8
JO - IEEE Transactions on Automatic Control
JF - IEEE Transactions on Automatic Control
ER -