Online Optimal Control with Linear Dynamics and Predictions: Algorithms and Regret Analysis

NeurIPS 2019 Yingying LiXin ChenNa Li

This paper studies the online optimal control problem with time-varying convex stage costs for a time-invariant linear dynamical system, where a finite lookahead window of accurate predictions of the stage costs are available at each time. We design online algorithms, Receding Horizon Gradient-based Control (RHGC), that utilize the predictions through finite steps of gradient computations... (read more)

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