Regular Papers

International Journal of Control, Automation and Systems 2022; 20(12): 4090-4099

Published online December 10, 2022

https://doi.org/10.1007/s12555-021-0544-8

© The International Journal of Control, Automation, and Systems

Event-triggered Adaptive Neural Control for Uncertain Nontriangular Nonlinear Systems with Time-varying Delays

Zhouzhou Xue, Zhaoxu Yu*, and Shugang Li

East China University of Science and Technology

Abstract

This paper addresses the adaptive tracking problem for a class of uncertain nontriangular nonlinear systems with time-varying delays. By employing some special techniques and mean value theorem, the nonlinear time-delay system in a nonaffine and nontriangular form is transformed into a new nonstrict-feedback nonlinear time-delay system for which backstepping control design becomes feasible. In particular, a novel event-triggered mechanism including saturation is presented to pursue the low communication burden and keep the competitive control performance. By combining Lyapunov-Razumikhin method, backstepping technique, and neural network (NN) approximation-based approach, the event-based adaptive neural control strategy is developed for this class of systems. The event-triggered control scheme guarantees that the tracking error remains in a small neighborhood of the origin while all the signals in closed-loop systems are semi-global uniformly ultimately bounded (SGUUB). Finally, an illustrative example is given to clarify the feasibility and effectiveness of the developed design methodology.

Keywords Adaptive control, event-triggered control, neural network, nonlinear time-delay system, Razumikhin lemma.

Article

Regular Papers

International Journal of Control, Automation and Systems 2022; 20(12): 4090-4099

Published online December 1, 2022 https://doi.org/10.1007/s12555-021-0544-8

Copyright © The International Journal of Control, Automation, and Systems.

Event-triggered Adaptive Neural Control for Uncertain Nontriangular Nonlinear Systems with Time-varying Delays

Zhouzhou Xue, Zhaoxu Yu*, and Shugang Li

East China University of Science and Technology

Abstract

This paper addresses the adaptive tracking problem for a class of uncertain nontriangular nonlinear systems with time-varying delays. By employing some special techniques and mean value theorem, the nonlinear time-delay system in a nonaffine and nontriangular form is transformed into a new nonstrict-feedback nonlinear time-delay system for which backstepping control design becomes feasible. In particular, a novel event-triggered mechanism including saturation is presented to pursue the low communication burden and keep the competitive control performance. By combining Lyapunov-Razumikhin method, backstepping technique, and neural network (NN) approximation-based approach, the event-based adaptive neural control strategy is developed for this class of systems. The event-triggered control scheme guarantees that the tracking error remains in a small neighborhood of the origin while all the signals in closed-loop systems are semi-global uniformly ultimately bounded (SGUUB). Finally, an illustrative example is given to clarify the feasibility and effectiveness of the developed design methodology.

Keywords: Adaptive control, event-triggered control, neural network, nonlinear time-delay system, Razumikhin lemma.

IJCAS
May 2024

Vol. 22, No. 5, pp. 1461~1759

Stats or Metrics

Share this article on

  • line

Related articles in IJCAS

IJCAS

eISSN 2005-4092
pISSN 1598-6446