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LPV-Koopman model predictive control: Modeling error and stability analysis
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DOI：10.1016/j.jfranklin.2026.108791.png)
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Abstract
En 中文
• Develop an input-enabled LPV–Koopman surrogate and a corresponding MPC framework for data-driven surrogates. • Establish a uniform error bound where the surrogate error scales linearly with the current state and input norms. • Prove asymptotic practical stability of the true closed loop and provide a sufficient condition for local exponential stability.
Keywords:
Koopman operator
LPV systems
Model predictive control
Stability analysis
Journal
J
IF:
3.7
Papers:
6.4K
Citations:
1.5W