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Chance Constrained Stochastic Optimal Control Of Discrete Time Linear Stochastic Systems With Applications In Multi-Satellite Operations, Shawn Priore

Electrical and Computer Engineering ETDs

Stochastic disturbances arise in a variety of engineering applications. For tractability, Gaussian disturbances are often assumed. However, this may not always be valid, such as when a disturbance exhibits heavy-tailed or skewed phenomena. As autonomous systems become more ubiquitous, non-Gaussian disturbances will become more common due to the compounding effects of sensing, actuation, and external forces. Despite this, little has been done to develop formal methods that are both computationally efficient and allow for analytical assurances with non-Gaussian disturbances. Addressing convex polytopic set acquisition and non-convex collision avoidance chance constraints with quantile and moment-based reformulations, this dissertation proposes novel stochastic …