Adaptive fuzzy output feedback dynamic surface control of interconnected nonlinear pure-feedback systems

Area of Science:

• Control Systems Engineering
• Nonlinear Dynamics
• Fuzzy Logic Systems

Background:

• Interconnected nonlinear pure-feedback systems often exhibit unknown uncertainties, making direct state measurement and control challenging.
• Decentralized output feedback control is crucial for managing complex systems where full state information is unavailable.

Purpose of the Study:

• To design an adaptive fuzzy decentralized output feedback control for nonlinear pure-feedback systems with unknown uncertainties.
• To address the challenge of unmeasured states by employing fuzzy logic systems and state observers.
• To ensure the stability and performance of the closed-loop system.

Main Methods:

• Fuzzy logic systems (FLS) are used to approximate unknown nonlinear functions within the system.
• A fuzzy state observer is designed to estimate immeasurable state variables.
• Adaptive backstepping dynamic surface control techniques are integrated for control scheme development.

Main Results:

• The proposed control scheme guarantees semi-globally uniformly ultimately boundedness for all closed-loop system variables.
• Observer and tracking errors are proven to converge to a small neighborhood of the origin.
• Simulation results demonstrate the effectiveness and advantages compared to existing methods.

Conclusions:

• The developed adaptive fuzzy decentralized output feedback control is effective for nonlinear pure-feedback systems.
• The approach successfully handles unknown uncertainties and unmeasured states.
• The method offers improved performance and stability for complex interconnected systems.