Adaptive fuzzy output-feedback controller design for nonlinear systems via backstepping and small-gain approach

Area of Science:

• Control Systems Engineering
• Nonlinear Dynamics
• Fuzzy Logic Systems

Background:

• Nonlinear systems often exhibit unmodeled dynamics, uncertainties, and dynamic disturbances.
• Ensuring practical stability in such complex systems is a significant challenge in control theory.

Purpose of the Study:

• To develop an adaptive output-feedback controller for nonlinear systems with unmodeled dynamics and dynamic disturbances.
• To guarantee input-to-state practical stability (ISpS) under relaxed assumption conditions for disturbances.

Main Methods:

• Utilizing fuzzy logic systems with an input-driven filter to approximate control signals.
• Employing an integrated backstepping technique for controller design.
• Applying input-to-state practical stability (ISpS) theory and the generalized small-gain approach.

Main Results:

• The proposed adaptive fuzzy controller ensures semi-globally uniformly ultimately bounded closed-loop system behavior.
• The controller exhibits robustness against unknown parameters and uncertain nonlinearities.
• A key advantage is the use of only three online adaptive parameters, irrespective of system order.

Conclusions:

• The developed adaptive fuzzy controller effectively addresses the ISpS problem for nonlinear systems with complex uncertainties.
• The approach offers a robust and parameter-efficient solution validated by simulation examples.