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Data-Driven Model Predictive Control of Time-Delay Systems
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DOI：10.1109/LCSYS.2026.3685309.png)
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Abstract
En 中文
This letter investigates a data-driven model predictive control (MPC) scheme for time-delay systems with unknown dynamics as well as input and state constraints. An infinite-horizon optimization problem is first formulated, in which a data-driven system representation is employed as a predictive model, and a delay-dependent state feedback controller is designed. By introducing a Lyapunov function, the control problem is systematically reduced to a tractable form, with a sufficient condition for the controller existence derived based on linear matrix inequality techniques. Then, the recursive feasibility of the MPC optimization and the stability of the resulting closed-loop system are rigorously established. Finally, the effectiveness of the proposed method is verified through numerical simulation.
Keywords:
Circuits
Feedback
Circuits and systems
Local area networks
Communication systems
Electronic mail
Feedback control
Switching systems
Message systems
Switches
Time-delay systems
data-driven control
model predictive control
stability
Journal
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IF:
2
Papers:
94
Citations:
5.0K
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