Abstract
This paper studies the problem of adaptive event-triggered dynamic output feedback fuzzy control for nonlinear networked control systems (NCSs). Two crucial factors, packet dropouts and random actuator failure, are taken into consideration simultaneously. Takagi-Sugeno (T-S) fuzzy model is introduced to describe considered systems. The Bernoulli random distribution process is employed to depict the phenomenon of data missing. A stochastic function, which is related to Markovian variables, is adopted to depict the actuator failure. An innovative adaptive event-triggered mechanism is introduced to save computational resource. In the framework of Lyapunov stability theory, an adaptive event-triggered fuzzy dynamic output feedback controller is designed to guarantee the stochastic stability and <formula><tex>$\mathcal{H}_{\infty}$</tex></formula> performance for considered systems. Finally, simulation results are provided to demonstrate the usefulness of the proposed control strategy.
| Original language | English |
|---|---|
| Journal | IEEE Transactions on Fuzzy Systems |
| DOIs | |
| Publication status | Accepted/In press - 2019 Jan 1 |
Keywords
- actuator failure
- Actuators
- Adaptation models
- Adaptive event-triggered mechanism
- Adaptive systems
- Delays
- Fuzzy control
- fuzzy dynamic output feedback control
- networked control systems (NCSs)
- Output feedback
- packet dropouts
- Symmetric matrices
ASJC Scopus subject areas
- Control and Systems Engineering
- Computational Theory and Mathematics
- Artificial Intelligence
- Applied Mathematics