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Robust MPC for polytopic uncertain systems via a high-rate network with the round-robin scheduling
Jianhua Wang1, Yiling Wang1, Xialai Wu1
1School of Engineering, Huzhou University, Huzhou, Zhejiang, China.
Peerj. Computer Science
|June 22, 2023
Summary
This study introduces robust model predictive control (RMPC) for uncertain systems using round-robin (RR) scheduling to prevent data collisions in high-rate networks. The proposed RMPC strategy guarantees system stability despite communication uncertainties.
Area of Science:
- Control Systems Engineering
- Networked Control Systems
- Systems Theory
Background:
- High-rate communication channels are prone to data collisions when multiple sensors transmit simultaneously.
- Round-robin (RR) scheduling is employed to manage data transmission order, allowing only one node access at a time.
- Robust Model Predictive Control (RMPC) is crucial for systems with polytopic uncertainties.
Purpose of the Study:
- To design a set of controllers within the RMPC framework for polytopic uncertain systems.
- To guarantee the asymptotic stability of the closed-loop system under RR scheduling in a high-rate communication channel.
- To address data collision issues inherent in shared communication networks.
Main Methods:
- Utilizing a token-dependent Lyapunov-like approach for stability analysis.
- Developing sufficient conditions by solving a terminal constraint set of an auxiliary optimization problem.
- Implementing an algorithm with both off-line and online components for sub-optimal solutions.
Main Results:
- The proposed RMPC strategy effectively guarantees the asymptotic stability of the closed-loop system.
- Sufficient conditions for stability are derived, considering the impact of RR scheduling.
- A practical algorithm is presented for finding feasible control solutions.
Conclusions:
- The developed RMPC strategy is effective for uncertain systems operating over shared high-rate communication channels with RR scheduling.
- The method provides a robust solution for maintaining system stability in the presence of communication constraints.
- Simulation examples validate the performance and applicability of the proposed control approach.
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