Novel Adaptive Event-Triggered Fuzzy Command Filter Control for Slowly Switched Nonlinear Systems With Constraints

Area of Science:

• Control Engineering
• Nonlinear Systems
• Fuzzy Logic

Background:

• Switched nonlinear systems present challenges due to state constraints and asynchronous switching.
• Traditional control methods struggle with complexity explosion and communication burdens.

Purpose of the Study:

• To develop an adaptive fuzzy control strategy for switched nonlinear systems with time-varying state constraints.
• To address asynchronous switching and reduce communication load.
• To ensure system stability and constraint satisfaction.

Main Methods:

• Unified Barrier Function (UBF) for state constraints.
• Command Filter-based backstepping for complexity.
• Event-triggered strategy with a novel threshold function for asynchronous switching.
• Admissible Edge-Dependent Average Dwell-Time (AED-ADT) method and Lyapunov stability analysis.

Main Results:

• Successfully handled time-varying state constraints without feasibility conditions.
• Mitigated the 'explosion of complexity' in backstepping control.
• Managed asynchronous switching and reduced communication burden effectively.
• Demonstrated bounded system signals and constraint satisfaction under the proposed switching rule.

Conclusions:

• The proposed adaptive fuzzy control algorithm ensures stability and constraint satisfaction for switched nonlinear systems.
• The novel event-triggered strategy and UBF are effective in handling system complexities.
• The algorithm shows superiority and is applicable to practical systems like ship maneuvering.