Adaptive Fuzzy Output Feedback Control for Switched Nonlinear Systems With Unmodeled Dynamics

Area of Science:

• Control Engineering
• Nonlinear Systems Theory
• Fuzzy Logic Systems

Background:

• Switched nonlinear systems often exhibit uncertainties and unmodeled dynamics, complicating control design.
• Observer-based output feedback is crucial when system states are not directly measurable.
• Adaptive fuzzy control offers a powerful framework for handling unknown nonlinearities.

Purpose of the Study:

• To develop a robust adaptive fuzzy control strategy for stabilizing uncertain nonlinear systems with arbitrary switching signals.
• To address the challenges of unmeasured states and unstructured uncertainties in these systems.
• To design an observer-independent of switching signals for state estimation.

Main Methods:

• Utilizing fuzzy logic systems to approximate unknown nonlinear functions and handle uncertainties.
• Employing an observer-based output feedback scheme for state estimation without direct measurement.
• Integrating adaptive backstepping design principles with a small-gain approach for robust control.
• Proving closed-loop system stability using common Lyapunov function theory and the small-gain theorem.

Main Results:

• A novel robust adaptive fuzzy output feedback stabilization control approach is successfully developed.
• The designed state observer effectively estimates unmeasured states, independent of switching signals.
• The proposed control strategy demonstrates robustness against unstructured uncertainties and unmodeled dynamics.
• Stability of the closed-loop system is rigorously proven through theoretical analysis.

Conclusions:

• The developed robust adaptive fuzzy control strategy provides effective stabilization for uncertain switched nonlinear systems.
• The observer-based output feedback scheme successfully overcomes the limitation of unmeasured states.
• Simulation results confirm the validity and performance of the proposed control method.