Observed-Based Adaptive Fuzzy Tracking Control for Switched Nonlinear Systems With Dead-Zone.

Area of Science:

• Control Systems Engineering
• Nonlinear Dynamics
• Fuzzy Logic Systems

Background:

• Switched nonlinear systems present challenges due to uncertainties, dead-zones, and immeasurable states.
• Adaptive control is crucial for managing system dynamics and ensuring stability.
• Fuzzy logic systems offer a powerful tool for approximating unknown nonlinearities.

Purpose of the Study:

• To develop an adaptive fuzzy output-feedback control strategy for uncertain switched nonlinear systems.
• To address issues of unknown nonlinearities, dead-zones, and immeasurable states.
• To guarantee system stability and output tracking performance.

Main Methods:

• Fuzzy logic systems for approximating unknown nonlinear functions.
• Switched fuzzy state observer for estimating immeasurable states.
• Adaptive backstepping design principle combined with average dwell time method.

Main Results:

• All closed-loop system variables are proven to be bounded under average dwell time switching signals.
• The system output achieves accurate tracking of the desired reference signal.
• Simulation results validate the effectiveness of the proposed adaptive fuzzy control approach.

Conclusions:

• The proposed adaptive fuzzy output-feedback control is effective for uncertain switched nonlinear systems.
• The method successfully handles unknown nonlinearities, dead-zones, and immeasurable states.
• The approach ensures robust stability and precise output tracking.