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Observer-based adaptive fuzzy output feedback control for functional constraint systems with dead-zone input.

Tianqi Yu¹, Lei Liu¹, Yan-Jun Liu¹

¹College of Science, Liaoning University of Technology, Jinzhou 121001, China.

Mathematical Biosciences and Engineering : MBE

|March 11, 2023

Summary

This summary is machine-generated.

This study presents an adaptive control for systems with unmeasurable states and unknown dead zones, ensuring stability within time-varying functional constraints. The method successfully addresses non-smooth inputs and guarantees system performance.

Keywords:

adaptive fuzzy control backstepping algorithm dead-zone input fuzzy state observer time-varying functional constraints (TFC)

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Area of Science:

Control Engineering
Systems Science
Applied Mathematics

Background:

Practical control systems often feature unmeasurable states and nonlinearities like dead zones.
Existing control methods struggle with time-varying functional constraints (TFC) that depend on system states and time.
Addressing these challenges is crucial for enhancing the robustness and applicability of control systems.

Purpose of the Study:

To develop an adaptive output feedback control strategy for functional constraint systems with unmeasurable states and unknown dead zone input.
To design an adaptive state observer capable of handling time-varying functional constraints.
To ensure system stability and constraint satisfaction in the presence of uncertainties and nonlinearities.

Main Methods:

An adaptive backstepping algorithm utilizing a fuzzy approximator was designed.
An adaptive state observer with time-varying functional constraints (TFC) was constructed to estimate unmeasurable states.
Time-varying integral barrier Lyapunov functions (iBLFs) were employed to enforce state constraints, and Lyapunov stability theory confirmed system stability.

Main Results:

The proposed control strategy effectively handles systems with unmeasurable states and unknown dead zone inputs.
The adaptive state observer successfully estimated system states under time-varying functional constraints.
The use of iBLFs guaranteed that system states remained within the specified constraint intervals.
Simulation experiments validated the feasibility and effectiveness of the developed control method.

Conclusions:

The developed adaptive output feedback control is effective for functional constraint systems with unmeasurable states and dead zones.
The integration of fuzzy approximation, adaptive observers, and iBLFs provides a robust solution for complex control challenges.
This research offers a more general and practical approach to control system design, validated by simulation.