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Adaptive finite-time neural control of nonstrict-feedback nonlinear systems with input dead-zone and output hysteresis

Author name : Mohamed Kharrat
Publication Date : 2025-03-09
Journal Name : International Journal of General Systems

Abstract

This paper explores the adaptive finite-time neural control issue for nonlinear systems with input dead zone and output hysteresis in nonstrict-feedback form. The unknown functions are estimated by employing the radial basis function neural networks (RBFNN) approach. A systematic adaptive finite-time control method is introduced using the backstepping technique and neural network approximation properties. The stability of the system is also examined by using semi-global practical finite-time stability theory. The established control approach guarantees the boundedness of all signals within the closed-loop system, enabling the system output to accurately follow the desired signal within a finite time framework while maintaining a small and bounded tracking error. Finally, simulation results are shown to demonstrate the efficacy of the suggested strategy.

Keywords

Adaptive Fuzzy, Actuator Fault, Command-Filter Control, control system, Lyapunov stability.

Publication Link

https://doi.org/10.1080/03081079.2024.2364623

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