Leveraging Stochasticity for Open Loop and Model Predictive Control of Spatio-Temporal Systems
Abstract
Stochastic spatio-temporal processes are prevalent across domains ranging from the modeling of plasma, turbulence in fluids to the wave function of quantum systems. This letter studies a measure-theoretic description of such systems by describing them as evolutionary processes on Hilbert spaces, and in doing so, derives a framework for spatio-temporal manipulation from fundamental thermodynamic principles. This approach yields a variational optimization framework for controlling stochastic fields. The resulting scheme is applicable to a wide class of spatio-temporal processes and can be used for optimizing parameterized control policies. Our simulated experiments explore the application of two forms of this approach on four stochastic spatio-temporal processes, with results that suggest new perspectives and directions for studying stochastic control problems for spatio-temporal systems.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jul 23, 2021
- Source ID
- 10.3390/e23080941
Entities
People
- Ethan N. Evans
- Evangelos A. Theodorou
- George I. Boutselis
- Marcus A. Pereira
Organizations
- Army Research Office
- Onassis Foundation