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Stochastic Nonlinear MPC with Gaussian Mixture Uncertainty Propagation
US & West ·
A new stochastic nonlinear model predictive control method for systems with additive noise is proposed. State distribution is approximated by Gaussian mixture with error bounds in Wasserstein distance. This yields closed-form expressions for expected costs and chance constraints, and the problem is solvable via nonlinear programming with correctness guarantees.
Why it matters
The method improves efficiency and robustness of control under uncertainty, relevant for managing large systems with stochastic disturbances.
The article discusses an architecture of a digital twin for nuclear systems, integrating multiple models (physics-based and data-driven) to support decision making, state estimation, predictive control, and real-time data processing. The twin must synchronize with the physical facility faster than its operational cycle.
Coordinated protests against Palantir took place in eight US cities, organized by nurses, patients, and activists. They demand that hospitals and authorities terminate contracts with Palantir due to concerns about surveillance, including its use by immigration services, and the company's growing presence in healthcare.
A new interdisciplinary paradigm, Dynamic Consent Engineering (DCE), is introduced, synthesizing Edward Bernays' principles of public relations with the S-E-E-D (Snowball, Equilibrium, Elasticity, Dominance) framework of system dynamics. The authors expand Bernaysian operational constraints into a four-dimensional resource matrix incorporating algorithmic media infrastructure and mathematically formalize how democratic institutions construct, optimize, and sustain political dominance.
