53 citations · 151 across the 36 of their papers we have counts for
8 papers · 1 filter
Stable and Robust LQR Design via Scenario Approach
Anna Scampicchio, Aleksandr Aravkin, Gianluigi Pillonetto
Linear Quadratic Regulator (LQR) design is one of the most classical optimal control problems, whose well-known solution is an input sequence expressed as a state-feedback. In this…
Robust Singular Smoothers For Tracking Using Low-Fidelity Data
Jonathan Jonker, Aleksandr Aravkin, James V. Burke +2
Tracking underwater autonomous platforms is often difficult because of noisy, biased, and discretized input data. Classic filters and smoothers based on standard assumptions of Gau…
Fast Robust Methods for Singular State-Space Models
Jonathan Jonker, Aleksandr Y. Aravkin, James V. Burke +2
State-space models are used in a wide range of time series analysis formulations. Kalman filtering and smoothing are work-horse algorithms in these settings. While classic algorith…
Generalized Kalman Smoothing: Modeling and Algorithms
A. Y. Aravkin, J. V. Burke, L. Ljung +2
State-space smoothing has found many applications in science and engineering. Under linear and Gaussian assumptions, smoothed estimates can be obtained using efficient recursions,…
Newton-Raphson Consensus for Distributed Convex Optimization
Damiano Varagnolo, Filippo Zanella, Angelo Cenedese +2
We address the problem of distributed uncon- strained convex optimization under separability assumptions, i.e., the framework where each agent of a network is endowed with a local…
Robust and Trend Following Student's t Kalman Smoothers
Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto
We present a Kalman smoothing framework based on modeling errors using the heavy tailed Student's t distribution, along with algorithms, convergence theory, open-source general imp…