Adaptive Fuzzy State/Output Feedback Control of Nonstrict-Feedback Systems: A Direct Compensation Approach.

Area of Science:

• Control Engineering
• Fuzzy Systems
• Nonlinear Control

Background:

• Nonstrict-feedback systems pose challenges for traditional control methods.
• Adaptive fuzzy control offers a flexible approach to complex dynamics.
• Direct compensation strategies aim to simplify controller design.

Purpose of the Study:

• To develop a differentiation-free adaptive fuzzy direct compensation control scheme.
• To address state/output feedback control for nonstrict-feedback systems.
• To ensure semi-global practical tracking stability.

Main Methods:

• Utilizing nominal adaptive fuzzy virtual controllers and low-pass filters to manage complexity and algebraic loops.
• Employing small time constants to bound filter errors without calculating filter error dynamics.
• Incorporating a supervisory linear high-gain control component.

Main Results:

• The proposed method successfully avoids the explosion of complexity and algebraic-loop problems.
• Semi-global practical tracking stability is achieved for both state and output feedback control.
• Stability criteria are demonstrated to be less stringent than existing variable-separation methods.

Conclusions:

• The differentiation-free adaptive fuzzy direct compensation control is feasible and effective for nonstrict-feedback systems.
• The approach simplifies stability analysis and controller implementation.
• Simulation results validate the efficacy of the proposed control schemes.