Event-based adaptive fuzzy control design for nonstrict-feedback nonlinear time-delay systems with state constraints.

Area of Science:

• Control Systems Engineering
• Nonlinear Dynamics
• Fuzzy Logic Systems

Background:

• Nonlinear time-delay systems with state constraints pose significant control challenges.
• Traditional control methods struggle with unknown system dynamics and computational complexity.

Purpose of the Study:

• To develop an event-triggered adaptive fuzzy control strategy for state-constrained nonlinear time-delay systems.
• To ensure system stability and satisfy prescribed state constraints efficiently.

Main Methods:

• Utilized fuzzy logic systems to approximate unknown system dynamics.
• Employed barrier Lyapunov functions to enforce state constraints.
• Integrated an event-triggered mechanism into the backstepping design to reduce control updates.
• Applied Lyapunov-Krasovskii functionals to manage time-delay effects.

Main Results:

• Achieved semi-globally uniformly ultimately bounded (SGUUB) stability for the closed-loop system.
• Effectively overcame the adverse effects of time delays.
• Reduced computational complexity by estimating the norm of the fuzzy weight vector.
• Demonstrated the method's effectiveness through two simulation examples.

Conclusions:

• The proposed event-triggered adaptive fuzzy control is effective for state-constrained nonlinear time-delay systems.
• The approach enhances stability, constraint satisfaction, and computational efficiency.
• The developed method offers a practical solution for complex control problems.