Adaptive Fuzzy Tracking Control With Global Prescribed-Time Prescribed Performance for Uncertain Strict-Feedback...

Area of Science:

• Control Systems Engineering
• Fuzzy Logic
• Nonlinear Systems

Background:

• Strict-feedback systems often face challenges with mismatched uncertainties.
• Previous adaptive control methods may have limitations in initial conditions and singularity issues.

Purpose of the Study:

• To develop adaptive fuzzy control for global prescribed performance and prescribed-time convergence in strict-feedback systems.
• To address initial value limitations and singularity issues in error transformation.

Main Methods:

• Design of prescribed-time prescribed performance functions to define error constraints.
• Introduction of a novel error transformation function.
• Development of controllers (with/without approximating structures) for prescribed-time convergence.
• Utilization of a Lyapunov-like energy function to eliminate semi-global boundedness issues.

Main Results:

• Achieved global prescribed performance with prescribed-time convergence for tracking error.
• Eliminated initial value limitations and singularity issues in error transformation.
• Demonstrated independence of settling time and initial conditions from system parameters.
• Overcame semi-global boundedness limitations of dynamic surface control.

Conclusions:

• The proposed adaptive fuzzy control strategies effectively ensure global prescribed performance and prescribed-time convergence.
• The novel error transformation and Lyapunov-like function offer significant improvements over existing methods.
• Validated effectiveness through numerical simulations on practical examples.