Neural networks-based adaptive fault-tolerant control for stochastic nonlinear systems with unknown backlash-like hysteresis and actuator faults

Kharrat, Mohamed

doi:10.1007/s12190-024-02042-2

J. Appl. Math. Comput.

2024

DOI: 10.1007/s12190-024-02042-2

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Neural networks-based adaptive fault-tolerant control for stochastic nonlinear systems with unknown backlash-like hysteresis and actuator faults

Mohamed Kharrat

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Echo state network-based adaptive control for nonstrict-feedback nonlinear systems with input dead-zone and external disturbance

Alhazmi,

Kharrat

2024

MATH

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This paper addressed the adaptive control problem for non-strict-feedback nonlinear systems with dead-zone and external disturbances. The design methodology integrated the backstepping technique with the approximation of unknown functions using an echo state network (ESN), enabling real-time adjustments. A comprehensive Lyapunov stability study was conducted to confirm the semi-globally uniformly ultimately boundedness (SGUUB) of all signals in the closed-loop system, ensuring that the tracking error converged to a small neighborhood of the origin. The effectiveness of the proposed method was further demonstrated through two examples, and error assessment criteria were utilized for comparisons with existing controllers.

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Echo state network-based adaptive control for nonstrict-feedback nonlinear systems with input dead-zone and external disturbance

Alhazmi,

Kharrat

2024

MATH

View full text Add to dashboard Cite

show abstract

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Neural networks-based adaptive fault-tolerant control for stochastic nonlinear systems with unknown backlash-like hysteresis and actuator faults

Cited by 1 publication

References 47 publications

Echo state network-based adaptive control for nonstrict-feedback nonlinear systems with input dead-zone and external disturbance

Echo state network-based adaptive control for nonstrict-feedback nonlinear systems with input dead-zone and external disturbance

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