Neural Network-Based Adaptive Finite-Time Control for Pure-Feedback Stochastic Nonlinear Systems with Full State Constraints, Actuator Faults, and Backlash-like Hysteresis
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In: Mathematics, Vol. 14, No. 1, 30, 01.2026.
Research output: Journal contributions › Journal articles › Research › peer-review
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TY - JOUR
T1 - Neural Network-Based Adaptive Finite-Time Control for Pure-Feedback Stochastic Nonlinear Systems with Full State Constraints, Actuator Faults, and Backlash-like Hysteresis
AU - Kharrat, Mohamed
AU - Mercorelli, Paolo
N1 - Publisher Copyright: © 2025 by the authors.
PY - 2026/1
Y1 - 2026/1
N2 - This paper addresses the tracking control problem for pure-feedback stochastic nonlinear systems subject to full state constraints, actuator faults, and backlash-like hysteresis. An adaptive finite-time control strategy is proposed, using radial basis function neural networks to approximate unknown system dynamics. By integrating barrier Lyapunov functions with a backstepping design, the method guarantees semi-global practical finite-time stability of all closed-loop signals. The strategy ensures that all states remain within prescribed limits while achieving accurate tracking of the reference signal in finite time. The effectiveness and superiority of the proposed approach are demonstrated through simulations, including a numerical example and a rigid robot manipulator system, with comparisons to existing methods highlighting its advantages.
AB - This paper addresses the tracking control problem for pure-feedback stochastic nonlinear systems subject to full state constraints, actuator faults, and backlash-like hysteresis. An adaptive finite-time control strategy is proposed, using radial basis function neural networks to approximate unknown system dynamics. By integrating barrier Lyapunov functions with a backstepping design, the method guarantees semi-global practical finite-time stability of all closed-loop signals. The strategy ensures that all states remain within prescribed limits while achieving accurate tracking of the reference signal in finite time. The effectiveness and superiority of the proposed approach are demonstrated through simulations, including a numerical example and a rigid robot manipulator system, with comparisons to existing methods highlighting its advantages.
KW - actuator faults
KW - backlash-like hysteresis
KW - finite-time stability
KW - full state constraints
KW - nonlinear systems
UR - http://www.scopus.com/inward/record.url?scp=105027266363&partnerID=8YFLogxK
U2 - 10.3390/math14010030
DO - 10.3390/math14010030
M3 - Journal articles
AN - SCOPUS:105027266363
VL - 14
JO - Mathematics
JF - Mathematics
SN - 2227-7390
IS - 1
M1 - 30
ER -