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Event-Triggered Adaptive Fuzzy Tracking Control With Guaranteed Transient Performance for MIMO Nonlinear Uncertain
IEEE Transactions on Cybernetics
|February 15, 2019
Summary
This study introduces an event-triggered adaptive fuzzy control for nonlinear systems, efficiently managing communication constraints and ensuring precise tracking performance without Zeno behavior.
Area of Science:
- Control Systems Engineering
- Nonlinear Dynamics
- Artificial Intelligence
Background:
- Nonlinear systems present significant control challenges, especially with multiple inputs and outputs (MIMO).
- Communication constraints and uncertainties complicate adaptive tracking control design.
- Event-triggered strategies are crucial for efficient resource utilization in control systems.
Purpose of the Study:
- To develop an event-triggered adaptive tracking control for MIMO nonlinear systems.
- To address rate-limited communication constraints and nonparametric uncertainties.
- To guarantee perfect tracking and transient performance.
Main Methods:
- Utilizing a relative threshold event-triggered strategy to manage communication constraints and avoid Zeno behavior.
- Developing an adaptive fuzzy control method with novel Lyapunov functions.
- Employing a computationally efficient fuzzy control scheme for the MIMO system.
Main Results:
- Successfully resolved communication resource constraints while avoiding Zeno behavior.
- Developed an adaptive fuzzy control method with reduced computational load.
- Proved global boundedness of all closed-loop signals.
Conclusions:
- The proposed event-triggered adaptive fuzzy control effectively guarantees output tracking and transient performance for MIMO nonlinear systems.
- The method efficiently handles communication constraints and system uncertainties.
- Simulation results validate the theoretical framework and practical effectiveness.
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