2017/01/06 by Gianluca Meneghello, Meneghello, Gianluca, Paolo Luchini +3
Earth and Planetary Sciences · Engineering · Environmental Science · #Advanced Control Systems Optimization #Climate variability and models #Dynamical Systems (math.DS) #FOS: Electrical engineering #FOS: Mathematics #Fluid Dynamics and Turbulent Flows #Meteorological Phenomena and Simulations #Optimization and Control (math.OC) #Reservoir Engineering and Simulation Methods #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1701.01777
openalex publication_date 2017/01/06 · openalex created_date 2022/10/07 · openalex updated_date 2026/07/28
A probabilistic framework is proposed for the optimization of efficient\nswitched control strategies for physical systems dominated by stochastic\nexcitation. In this framework, the equation for the state trajectory is\nreplaced with an equivalent equation for its probability distribution function\nin the constrained optimization setting. This allows for a large class of\ncontrol rules to be considered, including hysteresis and a mix of continuous\nand discrete random variables. The problem of steering atmospheric balloons\nwithin a stratified flowfield is a motivating application; the same approach\ncan be extended to a variety of mixed-variable stochastic systems and to new\nclasses of control rules.\n