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This research aims to develop a fixed-time adaptive control method for constrained nonlinear systems affected by input dead-zone and saturation.

January 18, 2026Applied Intelligence0 citationsOpen Access

Event-Triggered Fixed-Time Adaptive Control for Nonlinear Systems with Constraints

Event-triggered fixed-time adaptive control for constrained nonlinear systems with input dead-zone and saturation

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Adaptive control demonstrates fixed-time stability in nonlinear systems with input constraints, suggesting improved performance.

This research aims to develop a fixed-time adaptive control method for constrained nonlinear systems affected by input dead-zone and saturation.
Utilized radial basis function neural networks to identify unknown nonlinearities.
Approximated non-smooth nonlinearities with a smooth function and transformed to an affine form.
Developed an event-triggered adaptive control algorithm combining backstepping design and barrier Lyapunov functions.
Applied a varying threshold event-triggered condition to manage system dynamics under constraints.
Ensured that tracking errors converge to a smaller region within a fixed time.
Maintained boundedness of all variables in the closed-loop system.
Demonstrated effectiveness through two simulation examples.

Kharrat et al. (2026) studied this question.

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January 18, 2026Applied Intelligence0 citationsOpen Access

Event-triggered fixed-time adaptive control for constrained nonlinear systems with input dead-zone and saturation

View Full Paper

Ask AI

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Authors

Adaptive control demonstrates fixed-time stability in nonlinear systems with input constraints, suggesting improved performance.

This research aims to develop a fixed-time adaptive control method for constrained nonlinear systems affected by input dead-zone and saturation.
Utilized radial basis function neural networks to identify unknown nonlinearities.
Approximated non-smooth nonlinearities with a smooth function and transformed to an affine form.
Developed an event-triggered adaptive control algorithm combining backstepping design and barrier Lyapunov functions.
Applied a varying threshold event-triggered condition to manage system dynamics under constraints.
Ensured that tracking errors converge to a smaller region within a fixed time.
Maintained boundedness of all variables in the closed-loop system.
Demonstrated effectiveness through two simulation examples.

Kharrat et al. (2026) studied this question.

View Full Paper

Ask AI

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