| Abstract: |
| Since its introduction by Jan C. Willems, the concept of dissipativity has become a valuable tool for analyzing optimal and model predictive control problems.
While dissipativity and its relationship to the so-called turnpike property are well-established for deterministic problems, further theoretical development is required to extend these notions to stochastic settings.
In this talk, we introduce different forms of dissipativity based on stationarity concepts in distribution and random variables.
We show that these notions are suitable for analyzing the distributional and pathwise behavior of stochastic problems and highlight their connection to different stochastic turnpike properties.
Furthermore, we demonstrate how the proposed dissipativity and turnpike concepts can be utilized to analyze the performance of stochastic economic model predictive control schemes. |
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