Balancing Fuzzy Control Performance and Reachable-Set-Dependent Event-Triggered Communication

Area of Science:

• Control Systems Engineering
• Fuzzy Logic Systems
• Optimization Algorithms

Background:

• Takagi-Sugeno (T-S) fuzzy systems are susceptible to bounded external disturbances.
• Traditional fuzzy control schemes may suffer performance degradation under event-triggered frameworks due to limited information availability.

Purpose of the Study:

• To design a fuzzy controller and estimate the reachable set for T-S fuzzy systems under bounded disturbances.
• To develop a novel event-triggering condition for fuzzy control systems that ensures performance despite limited data.
• To establish a relationship between control performance and communication cost in event-triggered systems.

Main Methods:

• Design of a fuzzy controller to bound the closed-loop system's reachable set using an ellipsoid.
• Minimization of the bounding ellipsoid via two optimization algorithms.
• Proposal of a reachable-set-dependent event-triggering condition for enhanced fuzzy control.

Main Results:

• The proposed event-triggering condition ensures satisfactory control performance even with limited information.
• Explicit bounding ellipsoids for reachable sets are provided.
• A trade-off relationship between control performance and communication cost is established.

Conclusions:

• The novel event-triggering strategy effectively maintains control performance in T-S fuzzy systems.
• Communication rates can be reduced without compromising control performance when the reachable set is within safe limits.
• The proposed methods offer a viable approach for efficient and robust fuzzy control under event-triggered conditions.