Neural network-based adaptive fault-tolerant control for strict-feedback nonlinear systems with input dead zone and saturation
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In: Journal of the Franklin Institute, Vol. 362, No. 2, 107471, 01.2025.
Research output: Journal contributions › Journal articles › Research › peer-review
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TY - JOUR
T1 - Neural network-based adaptive fault-tolerant control for strict-feedback nonlinear systems with input dead zone and saturation
AU - Kharrat, Mohamed
AU - Krichen, Moez
AU - Alhazmi, Hadil
AU - Mercorelli, Paolo
N1 - Publisher Copyright: © 2024
PY - 2025/1
Y1 - 2025/1
N2 - This study investigates the issue of adaptive fault-tolerant neural control in strict-feedback nonlinear systems. The system is subjected to actuator faults, dead-zone and saturation. To model the unknown functions, radial basis function neural networks (RBFNN) are employed. The proposed approach utilizes a backstepping technique to formulate an adaptive fault-tolerant controller, drawing upon the Lyapunov stability theory and the approximation capabilities of RBFNN. The resultant controller guarantees the boundedness of all signals in the closed-loop system, ensuring precise tracking of the reference signal by the system output with a small, bounded error. Finally, simulation results are provided to illustrate the efficacy of the proposed strategy in addressing actuator faults, dead-zone, and saturation.
AB - This study investigates the issue of adaptive fault-tolerant neural control in strict-feedback nonlinear systems. The system is subjected to actuator faults, dead-zone and saturation. To model the unknown functions, radial basis function neural networks (RBFNN) are employed. The proposed approach utilizes a backstepping technique to formulate an adaptive fault-tolerant controller, drawing upon the Lyapunov stability theory and the approximation capabilities of RBFNN. The resultant controller guarantees the boundedness of all signals in the closed-loop system, ensuring precise tracking of the reference signal by the system output with a small, bounded error. Finally, simulation results are provided to illustrate the efficacy of the proposed strategy in addressing actuator faults, dead-zone, and saturation.
KW - Actuator fault
KW - Adaptive control
KW - Dead-zone
KW - Lyapunov function
KW - Nonlinear system
KW - One-link manipulator
KW - Saturation
KW - Engineering
UR - http://www.scopus.com/inward/record.url?scp=85212536130&partnerID=8YFLogxK
U2 - 10.1016/j.jfranklin.2024.107471
DO - 10.1016/j.jfranklin.2024.107471
M3 - Journal articles
AN - SCOPUS:85212536130
VL - 362
JO - Journal of the Franklin Institute
JF - Journal of the Franklin Institute
SN - 0016-0032
IS - 2
M1 - 107471
ER -