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Compensation-Based Output Feedback Control for Fuzzy Markov Jump Systems With Random Packet Losses
IEEE Transactions on Cybernetics
|August 10, 2021
Summary
This study introduces a new control method for fuzzy Markov jump systems experiencing data loss. The approach uses smoothing techniques and hidden Markov models to ensure system stability despite packet losses.
Area of Science:
- Control Theory
- Systems Engineering
- Artificial Intelligence
Background:
- Takagi-Sugeno fuzzy Markov jump systems are complex and prone to performance degradation due to packet losses in feedback channels.
- Existing control methods struggle to effectively compensate for random data loss in such systems.
Purpose of the Study:
- To develop a compensation-based output feedback control strategy for Takagi-Sugeno fuzzy Markov jump systems with packet losses.
- To ensure stochastic stability and strict dissipativity of the closed-loop system under random packet loss conditions.
Main Methods:
- Modeling packet loss using a Bernoulli process.
- Implementing a single exponential smoothing method for measurement prediction.
- Designing an asynchronous output feedback controller based on a hidden Markov model.
- Utilizing mode-dependent Lyapunov functions to derive stability conditions.
Main Results:
- Novel sufficient conditions for controller existence were derived, guaranteeing stochastic stability and strict dissipativity.
- An algorithm for optimizing the smoothing parameter was proposed.
- Simulation results validated the effectiveness and advantages of the proposed control approach.
Conclusions:
- The developed compensation-based output feedback control strategy effectively mitigates the impact of packet losses in Takagi-Sugeno fuzzy Markov jump systems.
- The method ensures system stability and performance through predictive measurement compensation and robust controller design.
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