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Event-triggered stabilization of uncertain scalar switched linear systems with bounded network delay
Rui Chen1, Jin Zhu1, Qiang Ling1
1Department of Automation, University of Science and Technology of China, Hefei 230027, China.
ISA Transactions
|March 15, 2022
Summary
This study stabilizes uncertain switched linear systems over digital networks, addressing network delays and mode mismatches. Novel event-triggered strategies reduce the required data rate for system stabilization.
Area of Science:
- Control Systems Engineering
- Networked Control Systems
- System Stability Analysis
Background:
- Switched linear systems are prevalent in control applications but present stability challenges.
- Digital communication networks introduce constraints like finite data rates and time-varying delays.
- Mode mismatch between system components due to network issues complicates controller design.
Purpose of the Study:
- To develop robust control strategies for stabilizing uncertain scalar switched linear systems.
- To analyze the impact of network-induced uncertainties (delay, data rate) on system stability.
- To design novel event-triggered sampling mechanisms for efficient data transmission.
Main Methods:
- Utilizing reachable set approximation and propagation techniques.
- Quantitatively assessing the influence of mode mismatch and model uncertainty.
- Developing integrated communication and control strategies.
- Proposing event-triggered sampling versus traditional periodic sampling.
Main Results:
- Established methods to guarantee system stability despite uncertainties.
- Quantified the effects of mode mismatch and model uncertainty.
- Demonstrated that event-triggered strategies require lower stabilizing bit rates.
- Validated the effectiveness of the proposed strategies through simulations.
Conclusions:
- The proposed methods effectively stabilize uncertain switched linear systems over digital networks.
- Event-triggered sampling offers a more efficient approach to data transmission for stabilization.
- The research provides valuable insights into managing networked control system complexities.
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